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As the labeling cost of object detection for medical images is very high, semi-supervised learning methods for medical images are investigated. In this paper, semi-supervised fine-grained object detection framework with transformer module (SFOD-Trans) is proposed for hepatic portal vein detection. It adopts Sparse R-CNN as the backbone. In detection model, the transformer module is introduced and contrastive loss is added to improve the performance of fine-grained object detection. In order to complete the information transfer both of labeled and unlabeled pictures, a new fusion module named normalized ROI fusion (NRF) is designed based on the characteristics of hepatic portal vein. We run a large number of experiments on a dataset of 1000 real CT scans. The results show that Average Precision (AP) and Average Recall (AR) of the proposed method reach 0.773 and 0.831 respectively with the 300 labeled and 1500 unlabeled samples. An overview of semi-supervised fine-grained object detection framework with transformer module (SFOD-Trans). There are two parallel branches to train supervised loss and semi-supervised loss respectively.

Water environment conditions directly support aquatic life. It is important to maintain a suitable water environment to improve the efficient use of water resources. Supersaturation of total dissolved gas (TDG) in the water will cause fish suffer from gas bubble disease and even mortalities. Measures should be taken to mitigate the adverse effect of supersaturated TDG. Considering the adsorption effect of porous medium, activated carbon (AC) was utilized in this experiment to explore the effect of AC on supersaturated TDG removal. The effects of AC properties, AC dosage, and initial TDG saturation were investigated. The results showed that adding AC in the water could effectively accelerate the supersaturated TDG removal rate, which was positively correlated with the AC specific surface area and dosage. Meanwhile, the average dissipation rate of TDG increased and then decreased with increasing initial TDG saturation. The adsorption characteristics of AC on supersaturated TDG were also explored. The maximum equilibrium adsorption capacity and removal rate were 0.262 mg/g and 48.5% respectively. It was concluded that the adsorption process of AC on supersaturated TDG conformed to the Langmuir equation and pseudo-first-order kinetic model. Recycling test indicated that the used AC could be reused after drying. It was hoped that this research could contribute to improving water environment and ensuring the healthy development of the aquatic livings.

With the improvement of the ability to acquire natural information, wireless sensor networks also need to transmit corresponding information in terms of collecting information. Wireless sensor nodes have great application prospects as a key component of wireless sensors. Therefore, different wireless sensors play an important decisive role in the operation of wireless network applications. With the continuous development of wireless sensor networks, existing wireless sensor network nodes exhibit limitations and shortcomings such as inflexible structure, low variability, and low versatility. Specifically, the learning and neural networks obtained by different artificial intelligence expert systems in computing technology are different. On the one hand, it can meet the needs of users for information systems to a certain extent, and on the other hand, it can also help accelerate the development of computer science. At present, the new generation of information technology industry is listed in the seven emerging strategic industries of the country. The new cloud computing technology has gradually expanded to important corporate governance capabilities in terms of information technology. The intelligent application of cloud computing technology replaces traditional enterprise management technology. Efficiency management and risk management can improve the quality and business capabilities of the entire enterprise, improve system applications according to the actual situation of the enterprise, improve system applications, and implement health and the sustainable development of the enterprise, thereby promoting the sustainable development of the computer technology industry.

Autism spectrum disorder (ASD) is a complex and heterogeneous neurodevelopmental disorder characterized by stereotyped behaviors, specific interests, and impaired social and communication skills. Synapses are fundamental structures for transmitting information between neurons. It has been reported that synaptic deficits, such as the increased or decreased density of synapses, may contribute to the onset of ASD, which affects the synaptic function and neuronal circuits. Therefore, targeting the recovery of the synaptic normal structure and function may be a promising therapeutic strategy to alleviate ASD symptoms. Exercise intervention has been shown to regulate the structural plasticity of synapses and improve ASD symptoms, but the underlying molecular mechanisms require further exploration. In this review, we highlight the characteristics of synaptic structural alterations in the context of ASD and the beneficial effects of an exercise intervention on improving ASD symptoms. Finally, we explore the possible molecular mechanisms of improving ASD symptoms through exercise intervention from the perspective of regulating synaptic structural plasticity, which contributes to further optimizing the related strategies of exercise intervention promoting ASD rehabilitation in future.

Background and purpose Ki-67 labeling index (LI) is an important indicator of tumor cell proliferation in glioma, which can only be obtained by postoperative biopsy at present. This study aimed to explore the correlation between Ki-67 LI and apparent diffusion coefficient (ADC) parameters and to predict the level of Ki-67 LI noninvasively before surgery by multiple MRI characteristics. Methods Preoperative MRI data of 166 patients with pathologically confirmed glioma in our hospital from 2016 to 2020 were retrospectively analyzed. The cut-off point of Ki-67 LI for glioma grading was defined. The differences in MRI characteristics were compared between the low and high Ki-67 LI groups. The receiver operating characteristic (ROC) curve was used to estimate the accuracy of each ADC parameter in predicting the Ki-67 level, and finally a multivariate logistic regression model was constructed based on the results of ROC analysis. Results ADCmin, ADCmean, rADCmin, rADCmean and Ki-67 LI showed a negative correlation (r = − 0.478, r = − 0.369, r = − 0.488, r = − 0.388, all P P P Conclusions There was a negative correlation between ADC parameters and Ki-67 LI, and the multivariate logistic regression model combined with peritumoral edema and ADC parameters could improve the prediction ability of Ki-67 LI.

The dissolved oxygen (DO) concentration is an important index of water quality. It has a significant impact on the biodegradation process in water and the survival of aquatic organisms. Low DO concentrations often exist and may result in a deterioration in water quality and an increase in wastewater treatment expenses. An analysis of the oxygen transfer efficiency as correlated with the flow characteristics of a falling jet could help to solve these problems. Experiments related to oxygen transfer along a falling water jet were conducted, and the effects of the flowrate ( Q ), falling height ( H ) and initial DO concentration ( c u ) were considered. The results demonstrated that a falling jet in air could be an effective way of improving the DO concentration. The results also indicated that the oxygen transfer efficiency is linearly dependent on c u and has a negative exponential relation with H . To deeply analyze the oxygen transfer process, the jet disturbance process was divided into 3 parts for the first time based on flow features: a smooth zone, turbulent zone and breakup zone. The results showed that the jet outlet velocity had a limited influence on the smooth zone height but assisted in jet breakup. Thereafter, a correlation modeling DO reaeration along the falling jet considering jet disturbance characteristics was obtained. This correlation was also applied to predict the aeration efficiency in experimental cases from the literature and showed good agreement with the reported results.

The acceleration of urbanization has brought significant changes to the urban underlying surface. As a result, the flood disaster caused by stormwater runoff has become increasingly prominent. The infiltration function of the permeable area can lead to flood disasters, but the extent and depth of the effect are still unclear. Therefore, based on the storm water management model (SWMM) and Green-Ampt infiltration model, this paper discussed the effect of improving soil saturated hydraulic conductivity (SSHC) and soil capillary suction head (SCSH) on the stormwater runoff process. The results show that the increase in SSHC and SCSH can significantly reduce runoff and increase infiltration. However, the improvement of SSHC can more effectively alleviate flood disasters compared with the improvement of SCSH. The change of SSHC has a significant effect on the stormwater runoff with a critical SSHC value while the effect can be ignored. In addition, there is a cross value; when the value of SSHC and SCSH is larger than the cross value, the difference between SSHC and SCSH in reducing runoff duration no longer exists. The critical value and cross value are not constant but change with the change of rainfall intensity. HIGHLIGHTS The effect of an urban underlying surface change on stormwater runoff is notionally studied.; Improving SSHC can reduce total runoff and increase total infiltration more effectively than improving SCSH.; There is an effect of rainfall intensity and urban IR in SSHC and SCSH on soil infiltration.; There exists a critical SSHC value, below which the change of SSHC has a significant effect on the stormwater runoff.

Social and economic development processes require large amounts of natural resources and in some cases seriously deteriorate river water quality. Since the reform and expansion era began, China has vigorously pursued socioeconomic development but neglected environmental protection. However, in recent years, improvements in environmental awareness and the implementation of environmental protection measures have led to a balanced relationship between economic development and the environment. In this study, the Yangtze River Basin and the Yellow River Basin were selected as research areas. We used a combination of canonical correlation analysis (CCA) and a distance-based influence assessment method to quantitatively assess the influence of socioeconomic development on river water quality. The results revealed a strong correlation between socioeconomic development and river water quality. The degree of influence of socioeconomic development on water quality varied not only temporally but also spatially due to differences in socioeconomic development and hydrometeorology in the two basins in North and South China. The average degree of influence in the Yangtze River Basin was between 0.22 and 0.27, and that in the Yellow River Basin was between 0.2 and 0.36. Moreover, the degree of influence in the Yangtze River Basin in the wet season was greater than that in the dry season, whereas the opposite pattern was observed in the Yellow River Basin. The degree of influence in both basins gradually declined after 2011, indicating that the coupling and coordination between socioeconomic development and environmental protection have continuously improved and that the water quality has gradually improved. By analysing the influences of various socioeconomic indicators on water quality, we found that the main factors that influence water quality are per capita GDP and urbanization rate in the Yangtze River Basin and urbanization rate in the Yellow River Basin. The results provide a basis for future sustainable development in the Yangtze River Basin and the Yellow River Basin.

Acute respiratory distress syndrome (ARDS) is a common cause of mortality in patients with acute kidney injury (AKI). Inflammatory crosstalk from the kidney to the lung has been shown to contribute to lung injury after AKI, but anti-inflammatory therapies have not been proven beneficial in human studies. Recently, AKI was shown to alter mitochondria and related metabolic pathways in the heart, but the impact of AKI on lung metabolism has not been investigated to our knowledge. In this study, we evaluated the metabolomic profile of the lung following renal ischemia and reperfusion to identify novel pathways that may be modifiable. We randomized C57BL/6 mice to 20 minutes of bilateral renal arterial clamping or sham operation under ketamine/xylazine anesthesia. At 4 hours after reperfusion, we found a significant increase in markers of lung injury, as well as significant metabolomic changes across lung, kidney, plasma and bronchoalveolar lavage fluid (BALF) compared to shams. Comparative analyses revealed that the fatty acid oxidation pathway was the most significantly altered metabolic pathway, a finding which is consistent with mitochondrial dysfunction systemically and in the lung. These metabolomic changes correlated with the extracellular accumulation of the mitochondrial damage associated molecular patterns (mtDAMPs), mitochondrial DNA (mtDNA) and transcription factor A, mitochondria (TFAM). Finally, we found that intraperitoneal injection of renal mtDAMPs caused metabolomic changes consistent with mitochondrial dysfunction in the lung in vivo. Mitochondrial function and mtDAMPs warrant further investigation as potential therapeutic targets in preventing lung injury because of AKI.

Critical illness leads to millions of deaths worldwide each year, with a significant surge due to the COVID-19 pandemic. Patients with critical illness are frequently associated with systemic metabolic disorders and malnutrition. The idea of intervention for critically ill patients through enteral and parenteral nutrition has been paid more and more attention gradually. However, current nutritional therapies focus on evidence-based practice, and there have been lacking holistic approaches for nutritional support assessment. Metabolomics is a well-established omics technique in system biology that enables comprehensive profiling of metabolites in a biological system and thus provides the underlying information expressed and modulated by all other omics layers. In recent years, with the development of high-resolution and accurate mass spectrometry, metabolomics entered a new "generation", promoting its broader applications in critical care nutrition. In this review, we first described the technological development and milestones of next-generation metabolomics in the past 20 years. We then discussed the emerging roles of next-generation metabolomics in advancing our understanding of critical care nutrition, such as nutritional deficiency risk evaluation, metabolic mechanisms of nutritional therapies, and novel nutrition target identification.

The proper water chemical composition of aquaculture water is very important for fish farming in reservoirs or fish multiplication stations. Gas bubble disease (GBD) is mainly caused by total dissolved gas supersaturation (TDGS) in water and is a common problem that affects the healthy growth of fish. Extensive measures have been taken to mitigate TDGS levels in water where fish live, while methods for quantitatively evaluating the mitigation effect of the proposed measures on fish exposed to TDGS are still lacking. In this paper, an activated carbon (AC) adsorption experiment for supersaturated total dissolved gas (TDG) dissipation was conducted, and the experimental results indicated that AC addition could effectively accelerate supersaturated TDG dissipation. Based on fish tolerance experiments conducted by Huang (2010), two models, including a mortality risk degree evaluation model and a mortality rate calculation model, were developed to quantitatively evaluate the mortality risk mitigation effect of AC addiction on fish exposed to unsteady TDGS levels. Application of the results of the mortality risk degree evaluation model has shown that AC addition can help alleviate the mortality risk of fish suffering from TDGS. Application of the results of the mortality rate calculation model has also demonstrated that the final mortality rate of the fish group in the case with AC addition was lower than that of the case without added AC, and the final mortality rate decreased as the specific surface area and dosage of AC increased. Furthermore, an equation that related the required AC mass and a given harvested fish mass was established. This paper provides a reference for evaluating the effects of various mitigation measures to alleviate the risk posed to fish by TDGS.

Depression is a widespread and persistent psychiatric disease. Due to various side effects and no curative treatments of conventional antidepressant drugs, botanical medicines have attracted considerable attention as a complementary and alternative approach. The pathogenesis of depression is quite complicated and unclear. Metabolomics is a promising new technique for the discovery of novel biomarkers for exploring the potential mechanisms of diverse diseases and assessing the therapeutic effects of drugs. In this article, we systematically reviewed the study of botanical medicine for the treatment of depression using metabolomics over a period from 2010 to 2019. Additionally, we summarized the potential biomarkers and metabolic pathways associated with herbal medicine treatment for depression. Through a comprehensive evaluation of herbal medicine as novel antidepressants and understanding of their pharmacomechanisms, a new perspective on expanding the application of botanical medicines for the treatment of depression is provided.

Supersaturated water can adversely affect many species of fish and can sometimes lead to death. In the present study, we established an experimental platform on the downstream section of the Dagangshan Hydropower Station on the Dadu River. During flood discharge at the Dagangshan Hydropower Station, the river water supersaturation concentration at the experimental site was monitored, and a unique fish in the river section was selected for a cage experiment. Juvenile fish die under the 110% gas supersaturation conditions in the river, accompanied by symptoms of bubble disease. After the end of flood discharge, the remaining experimental fish were placed in clean water for approximately 180 days, and all the fish died. Exposing the experimental fish to a 127% concentration test tank in the laboratory revealed that the onset of death, semi-lethal time and total death time were 6.7 hours, 12 hours, 31.5 hours, respectively. The test fish that were exposed to supersaturated water for 6 hours were placed in clean water and tested every hour, and the change was minimal. Six-hour exposure may cause irreversible damage to the experimental fish.

Light-oxygen-voltage (LOV) proteins are ubiquitous photoreceptors that can interact with other regulatory proteins and then mediate their activities, which results in cellular adaptation and subsequent physiological changes. Upon blue-light irradiation, a conserved cysteine (Cys) residue in LOV covalently binds to flavin to form a flavin-Cys adduct, which triggers a subsequent cascade of signal transduction and reactions. We found a group of natural Cys-less LOV-like proteins in magnetotactic bacteria (MTB) and investigated its physiological functions by conducting research on one of these unusual LOV-like proteins, Amb2291, in Magnetospirillum magneticum. In-frame deletion of amb2291 or site-directive substitution of alanine-399 for Cys mutants impaired the protective responses against hydrogen peroxide, thereby causing stress and growth impairment. Consequently, gene expression and magnetosome formation were affected, which led to high sensitivity to oxidative damage and defective phototactic behaviour. The purified wild-type and A399C-mutated LOV-like proteins had similar LOV blue-light response spectra, but Amb2291A399C exhibited a faster reaction to blue light. We especially showed that LOV-like protein Amb2291 plays a role in magnetosome synthesis and resistance to oxidative stress of AMB-1 when this bacterium was exposed to red light and hydrogen peroxide. This finding expands our knowledge of the physiological function of this widely distributed group of photoreceptors and deepens our understanding of the photoresponse of MTB. KEY POINTS: • We found a group of Cys-less light-oxygen-voltage (LOV) photoreceptors in magnetotactic bacteria, which prompted us to study the light-response and biological roles of these proteins in these non-photosynthetic bacteria. • The Cys-less LOV-like protein participates in the light-regulated signalling pathway and improves resistance to oxidative damage and magnetic crystal biogenesis in Magnetospirillum magneticum. • This result will contribute to our understanding of the structural and functional diversity of the LOV-like photoreceptor and help us understand the complexity of light-regulated model organisms.

Herein, warm drawing technology assisted by an electric current heating system is proposed to minimize the formation of wrinkles and cracks on the surface of Q390A high-strength steel V-shaped stiffeners during cold forming. V-shaped stiffeners with excellent properties were obtained by elevating the forming temperature and improving the material plasticity. The influence of temperature and tensile rate on the mechanical properties of the Q390A high-strength steel at 400-800°C was investigated. The effects of blankholder force and friction coefficient on the formed parts were simulated and analyzed by the finite element simulation software DYNAFORM. The law of heating and cooling for the formed parts during the forming process was studied through the electric current heating experiments. The forming temperature was controlled from 530 to 720 °C as the current density was maintained in the range from 7.3 to 8.5 A/mm2. Surface oxidation, cracks, sheet warping degree, sectional thickness distribution, mechanical properties, and microstructure of the V-shaped stiffeners formed at 400 to 700 °C were analyzed. The results show that the V-shaped stiffeners formed at 600 °C possess excellent overall properties.

Several superhigh dams (greater than 200 m in height) and many high dams have been built in the upper Yangtze River basin in recent years, and these dams have made total dissolved gas (TDG) supersaturation a serious environmental problem. A few studies have examined the tolerance and avoidance characteristics of rare and endemic fish in TDG‐supersaturated water in the upper Yangtze River over the past 10 years. These studies focused on specific species and specific sizes and did not identify a regular pattern that can be applied to all resident fish in the upper Yangtze River. However, elucidating this type of pattern is crucial for fishery management and dam operations in the upper Yangtze River. Data on the median lethal time (LT₅₀), horizontal avoidance percentage, and vertical water depth of three rare and endemic species in the upper Yangtze River from previous studies were used in the current work. An exponential relationship was found between LT₅₀ of fish and TDG supersaturation. The avoidance percentage of fish has a linear relationship with TDG supersaturation. Fish in the upper Yangtze River can use depth compensation to avoid the threat of TDG when the saturation is 130% or above but rarely avoid the threat of TDG when the saturation is less than 125%. We also described the tolerance and avoidance characteristics of fish in a TDG‐supersaturated river downstream from a super‐high dam. When the dam discharged a two‐year flood, the LT₅₀ values of fish downstream ranged from 9.1 to 27.5 hr regardless of depth compensation. The avoidance percentage of resident fish ranged from 8.4 to 44.8%. The resident fish swam to a water depth of 2.43–3.33 m to avoid the threat of TDG.

Multiple studies have suggested that long non-coding RNAs (lncRNAs) are involved in the development and progression of osteoarthritis (OA). However, how lncRNA SNHG1 regulates OA remains unknown. This study aimed to explore how SNHG1 regulates chondrocyte apoptosis and inflammation. Our data showed that H

Metabolomics has emerged as a powerful new tool in precision medicine. No studies have yet been published on the metabolomic changes in cerebrospinal fluid (CSF) produced by acute endurance exercise. CSF and plasma were collected from 19 young active adults (13 males and 6 females) before and 60 min after a 90-min monitored outdoor run. The median age, BMI, and VO

Background and objective Radioiodine therapy (RAI) is one of the most common treatment solutions for Graves’ disease (GD). However, many patients will develop hypothyroidism as early as 6 months after RAI. This study aimed to implement machine learning (ML) algorithms for the early prediction of post-RAI hypothyroidism. Methods Four hundred and seventy-one GD patients who underwent RAI between January 2016 and June 2019 were retrospectively recruited and randomly split into the training set (310 patients) and the validation set (161 patients). These patients were followed for 6 months after RAI. A set of 138 clinical and lab test features from the electronic medical record (EMR) were extracted, and multiple ML algorithms were conducted to identify the features associated with the occurrence of hypothyroidism 6 months after RAI. Results An integrated multivariate model containing patients’ age, thyroid mass, 24-h radioactive iodine uptake, serum concentrations of aspartate aminotransferase, thyrotropin-receptor antibodies, thyroid microsomal antibodies, and blood neutrophil count demonstrated an area under the receiver operating curve (AUROC) of 0.72 (95% CI: 0.61–0.85), an F1 score of 0.74, and an MCC score of 0.63 in the training set. The model also performed well in the validation set with an AUROC of 0.74 (95% CI: 0.65–0.83), an F1 score of 0.74, and a MCC of 0.63. A user-friendly nomogram was then established to facilitate the clinical utility. Conclusion The developed multivariate model based on EMR data could be a valuable tool for predicting post-RAI hypothyroidism, allowing them to be treated differently before the therapy. Further study is needed to validate the developed prognostic model at independent sites.

Hydropower development can significantly mitigate climate change and reduce carbon emissions, but it can also have substantial negative impacts on river environments and fish biodiversity. Fish passage facilities are built to ensure sustainable hydropower development and the biodiversity of fish populations. The locations of the entrances to these facilities play a key role in their efficiency. This study presents a reliable approach that combines the swimming ability of fish and a numerical flow field simulation to determine the optimal location for a fish passage facility entrance. In this study, we used the Gujun Reservoir upstream of the Yangtze River as a case study. A field experiment was conducted, and the swimming abilities of eight endemic fish species in the upstream region of the Yangtze River were measured. Among the tested species, the fastest induced swimming speed (0.14 m/s) was achieved by Glyptothorax sinense, while the slowest critical swimming speed (0.30 m/s) was observed for Paracobitis potanini. We propose that the velocity near the fish passage facility entrance should be higher than the maximum induced swimming speed and lower than the minimum critical swimming speed, making the suitable range between 0.14 and 0.30 m/s. On this basis, velocity fields 500 m downstream of the dam of the Gujun Reservoir under 4 operating conditions with discharge flows of 5.7 m

During flood discharges of upstream dams in the Yangtze River, the pelagic fish have a stress risk from total dissolved gas (TDG) supersaturation in the river water. This study took the silver carp as the object and systematically evaluated the effects of TDG supersaturation levels and exposure time on their critical swimming speed (Ucrit) at different temperatures. The external symptoms of gas bubble disease were found when TDG levels exceeded 130%. Both exposure time and TDG level did not significantly impact the Ucrit of fish under 6 days of non-lethal exposure (110%, 120%, 130% TDG) with lower or higher water temperature. Significant differences in Ucrit were found among different exposure times at 11.0 ± 1.0°C under 10 hours of lethal exposure (135%, 140%, 150% TDG) and the Ucrit reduced by 59.88%, 83.32%, and 92.40%, respectively. TDG level had a significant impact on the Ucrit at 21.0 ± 1.0°C when exposure time exceeded 8 hours. Ucrit at 21.0 ± 1.0°C water were significantly greater than those at 11.0 ± 1.0°C water where conditions had the same TDG supersaturation and exposure time. Differences in Ucrit between temperatures ranged from 3.24 to 6.12 BL/s under non-lethal exposure and from 6.38 to 13.88 BL/s under lethal exposure. The results of this study can provide a reference for fish conservation during flood discharge.

Background The chemical composition of human milk has long-lasting effects on brain development. We examined the prognostic value of the human milk metabolome and exposome in children with the risk of neurodevelopmental delay (NDD). Methods This retrospective cohort study included 82 mother–infant pairs (40 male and 42 female infants). A total of 59 milk samples were from mothers with typically developing children and 23 samples were from mothers of children at risk. Milk samples were collected before 9 months of age (4.6 ± 2.5 months, mean ± SD). Neurocognitive development was assessed by maternal report at 14.2 ± 3.1 months using the Ages and Stages Questionnaires-2. Results Metabolome and exposome profiling identified 453 metabolites and 61 environmental chemicals in milk. Machine learning tools identified changes in deoxysphingolipids, phospholipids, glycosphingolipids, plasmalogens, and acylcarnitines in the milk of mothers with children at risk for future delay. A predictive classifier had a diagnostic accuracy of 0.81 (95% CI: 0.66–0.96) for females and 0.79 (95% CI: 0.62–0.94) for males. Conclusions Once validated in larger studies, the chemical analysis of human milk might be added as an option in well-baby checks to help identify children at risk of NDD before the first symptoms appear. Impact Maternal milk for infants sampled before 9 months of age contained sex-specific differences in deoxysphingolipids, sphingomyelins, plasmalogens, phospholipids, and acylcarnitines that predicted the risk of neurodevelopmental delay at 14.2 months of age. Once validated, this early biosignature in human milk might be incorporated into well-baby checks and help to identify infants at risk so early interventions might be instituted before the first symptoms appear.

First started in 1931, the Continuous Plankton Recorder (CPR) Survey is the longest-running and most geographically extensive marine plankton sampling program in the world. This pilot study investigates the feasibility of biomonitoring the spatiotemporal trends of marine pollution using archived CPR samples from the North Pacific. We selected specimens collected from three different locations (British Columbia Shelf, Northern Gulf of Alaska, and Aleutian Shelf) in the North Pacific between 2002 and 2020. Comprehensive profiling of the plankton chemical exposome was conducted using liquid and gas chromatography coupled with tandem mass spectrometry (LC-MS/MS and GC-MS/MS). Our results show that phthalates, plasticizers, persistent organic pollutants (POPs), pesticides, pharmaceuticals, and personal care products were present in the plankton exposome, and that many of these pollutants have decreased in amount over the last two decades, which was most pronounced for tri-n-butyl phosphate. In addition, the plankton exposome differed significantly by regional human activities, with the most polluted samples coming from the nearshore area. Exposome-wide association analysis revealed that bioaccumulation of environmental pollutants was highly correlated with the biomass of different plankton taxa. Overall, this study demonstrates that exposomic analysis of archived samples from the CPR Survey is effective for long-term biomonitoring of the spatial and temporal trends of environmental pollutants in the marine environment.

Retinal vessel segmentation remains a challenging task because the morphology of the retinal vessels reflects the health of a person, which is essential for clinical diagnosis. Therefore, achieving accurate segmentation of the retinal vessel shape can determine the patient’s physical condition in a timely manner and can prevent blindness in patients. Since the traditional retinal vascular segmentation method is manually operated, this can be time-consuming and laborious. With the development of convolutional neural networks, U-shaped networks (U-Nets) and variants show good performance in image segmentation. However, U-Net is prone to feature loss due to the operation of the encoder convolution layer and also causes the problem of mismatch in the processing of contextual information features caused by the skip connection part. Therefore, we propose an improvement of the retinal vessel segmentation method based on U-Net to segment retinal vessels accurately. In order to extract more features from encoder features, we replace the convolutional layer with ResNest network structure in feature extraction, which aims to enhance image feature extraction. In addition, a Depthwise FCA Block (DFB) module is proposed to deal with the mismatched processing of local contextual features by skip connections. Combined with the two public datasets on retinal vessel segmentation, namely DRIVE and CHASE_DB1, and comparing our method with a larger number of networks, the experimental results confirmed the effectiveness of the proposed method. Our method is better than most segmentation networks, demonstrating the method’s significant clinical value.

Brain function relies on efficient communications between distinct brain systems. The pathology of major depressive disorder (MDD) damages functional brain networks, resulting in cognitive impairment. Here, we reviewed the associations between brain functional connectome changes and MDD pathogenesis. We also highlighted the utility of brain functional connectome for differentiating MDD from other similar psychiatric disorders, predicting recurrence and suicide attempts in MDD, and evaluating treatment responses. Converging evidence has now linked aberrant brain functional network organization in MDD to the dysregulation of neurotransmitter signaling and neuroplasticity, providing insights into the neurobiological mechanisms of the disease and antidepressant efficacy. Widespread connectome dysfunctions in MDD patients include multiple, large-scale brain networks as well as local disturbances in brain circuits associated with negative and positive valence systems and cognitive functions. Although the clinical utility of the brain functional connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments, and clinical outcomes of MDD.

In this study, we investigated the molecular characteristics and spatio-temporal dynamics of GII.P17-GII.17 norovirus in Zhoushan Islands during 2013–2018. We collected 1849 samples from sporadic acute gastroenteritis patients between January 2013 and August 2018 in Zhoushan Islands, China. Among the 1849 samples, 134 (7.24%) samples were positive for human norovirus (HuNoV). The complete sequence of GII.17 VP1 gene was amplified from 31 HuNoV-positive samples and sequenced. A phylogenetic tree was constructed based on the full-length sequence of the VP1 gene. Phylogenetic analysis revealed that the GII.17 genotype detected during 2014–2018 belongs to the new GII.17 Kawasaki variant. Divergence analysis revealed that the time of the most recent common ancestor (TMRCA) of GII.17 in Zhoushan Islands was estimated to be between 1997 and 1998. The evolutionary rate of the VP1 gene of the GII.17 genotype norovirus was 1.14 × 10–3 (95% HPD: 0.62–1.73 × 10–3) nucleotide substitutions/site/year. The spatio-temporal diffusion analysis of the GII.17 genotype identified Hong Kong as the epicenter for GII.17 dissemination. The VP1 gene sequence of Zhoushan Island isolates correlated with that of Hong Kong and Japan isolates.

The accurate diagnosis of small cell lung cancer (SCLC) at initial presentation is essential to ensure appropriate treatment. No validated blood biomarkers that could distinguish SCLC from non-small cell lung cancer (NSCLC) has yet been developed. Dried blood spot (DBS) microsampling has gained increasing interest in biomarkers discovery. In this study, we first performed metabolomic profiling of DBS samples from 37 SCLC, 40 NSCLC, and 37 controls. Two gender-specific multianalyte discriminant models were established for males and females, respectively to distinguish SCLC from NSCLC and controls. The receiver operator characteristic (ROC) curve analysis showed the diagnostic accuracy of 95% (95% CI: 83%-100%) in males SCLC using five metabolites in DBS and 94% (95% CI: 74%-100%) for females using another set of five metabolites. The robustness of the models was confirmed by the random permutation tests (P < 0.01 for both). The performance of the discriminant models was further evaluated using a validation cohort with 78 subjects. The developed discriminant models yielded an accuracy of 91% and 81% for males and females, respectively, in the validation cohort. Our results highlighted the potential clinical utility of the metabolomic profiling of DBS as a convenient and effective approach for the diagnosis of SCLC.

Ciprofloxacin (CIP) is a synthetically produced and widely prescribed antibiotic. Due to incomplete metabolism and gut absorption, a significant portion of the consumed CIP is excreted and released into the environment through wastewater. Vetiver grass has been reported to tolerate many organic and inorganic pollutants. Our objectives were to evaluate the potential of vetiver grass to remove CIP from aquatic media with the ultimate goal of developing a plant-based method for wastewater treatment. We also examined the potential degradation/transformation of CIP in the plant and the metabolic pathways impacted by CIP. Results show that vetiver grass removed more than 80% CIP within 30 days. Ciprofloxacin elicited a stress response by inducing antioxidant enzymes, and metabolic profiling indicated an impact on key metabolic pathways. Transformation products of CIP in vetiver tissue indicate the potential role of root-associated microorganisms as well as plant metabolism in CIP degradation.

Plant growth promoting bacteria (PGPB) provide multiple benefits in agriculture by enhancing crop productivity and nutrient content and suppressing the growth of pathogens. Development of beneficial plant-microbe interactions based on genomics, transcriptomics, proteomics and metabolomic data of both PGPB and host will lead to optimized microbial inoculants for enhancing crop yield and nutrient content. PGPB are promoted as a green technology which will reduce the use of chemical fertilizers thereby improving soil health. Although a significant increase in the use of PGPB in agriculture was observed in the last two decades, there is a dearth of long-term studies addressing the effects of PGPB on existing microbial community structure. It is likely that most or all PGPB are resistant to common antibiotics used to treat human diseases. Antibiotic resistance of PGPB may be due to the presence of antibiotic resistance genes and intrinsic resistance due to the presence of efflux pumps. The biological significance of resistance to antibiotics and metals and their relation to plant growth promoting activity, if any, is not known. The consequences of harboring antibiotic resistance may be negative if the trait is transferred to other soil or environmental bacteria. Strategies to develop PGPB strains with useful traits of plant growth promotion but without resistance to common antibiotics used by humans, would enhance agricultural productivity without the negative effects on the environment. Alternately, harboring antibiotic resistance may be positive if it is due to intrinsic resistance involving proteins which also have other functions. Antibiotic resistance of PGPB may be an essential trait if it is related to their plant growth promoting activity. Overall, there is a need to conduct large-scale screening of PGPB for antibiotic resistance and long-term studies to see the effect of the introduction of biofertilizers on native soil microbial community.

The feasibility of composite-activated coal gangue (CACG) as the primary cementitious material for concrete was experimentally studied in this paper. The effects of concrete strength grade on slump and slump flow, compressive strength, splitting tensile strength, axial compressive strength, elastic modulus, and drying shrinkage of alkali-activated coal gangue concrete (AACGC) were experimentally investigated. Experimental results indicated that the slump and slump flow of the AACGC were smaller than that of ordinary Portland cement concrete (OPCC). The mechanical properties of the AACGC were superior to those of the OPCC. The compressive strength, splitting tensile strength, axial compressive strength, and elastic modulus of the AACGC were 1.17 times, 1.04 times, 1.47 times, and 1.04 times those of the OPCC, respectively. With the increase in concrete strength grade, the mechanical properties of the AACGC have gradually increased. The difference in failure modes of axial compressive strength between the AACGC and OPCC was analyzed. Moreover, the empirical formulas of the elastic modulus and compressive strength for the OPCC in various regions codes were summarized, and found that the empirical formula in GB 50010-2002 code and EN 1922 Eurocode 2 was also applicable to the AACGC. Finally, the mass-loss rate and drying shrinkage for the AACGC at different concrete strength grades were systematically analyzed, and a hyperbolic prediction model was proposed to reflect the drying shrinkage behavior of the AACGC.