Ultrasensitive Point-of-Care Detection of Protein Markers Using an Aptamer-CRISPR/Cas12a-Regulated Liquid Crystal Sensor (ALICS).

Despite extensive efforts, point-of-care testing (POCT) of protein markers with high sensitivity and specificity and at a low cost remains challenging. In this work, we developed an aptamer-CRISPR/Cas12a-regulated liquid crystal sensor (ALICS), which achieved ultrasensitive protein detection using a smartphone-coupled portable device. Specifically, a DNA probe that contained an aptamer sequence for the protein target and an activation sequence for the Cas12a-crRNA complex was prefixed on a substrate and was released in the presence of target. The activation sequence of the DNA probe then bound to the Cas12a-crRNA complex to activate the collateral cleavage reaction, producing a bright-to-dark optical change in a DNA-functionalized liquid crystal interface. The optical image was captured by a smartphone for quantification of the target concentration. For the two model proteins, SARS-CoV-2 nucleocapsid protein (N protein) and carcino-embryonic antigen (CEA), ALICS achieved detection limits of 0.4 and 20 pg/mL, respectively, which are higher than the typical sensitivity of the SARS-CoV-2 test and the clinical CEA test. In the clinical sample tests, ALICS also exhibited superior performances compared to those of the commercial ELISA and lateral flow test kits. Overall, ALICS represents an ultrasensitive and cost-effective platform for POCT, showing a great potential for pathogen detection and disease monitoring under resource-limited conditions.

Sustaining Irrigation Supplies through Immobilization of Groundwater Arsenic In Situ.

Geogenic arsenic (As) in groundwater is widespread, affecting drinking water and irrigation supplies globally, with food security and safety concerns on the rise. Here, we present push-pull tests that demonstrate field-scale As immobilization through the injection of small amounts of ferrous iron (Fe) and nitrate, two readily available agricultural fertilizers. Such injections into an aquifer with As-rich (200 ± 52 µg/L) reducing groundwater led to the formation of a regenerable As reactive filter in situ, producing 15 m3 of groundwater meeting the irrigation water quality standard of 50 µg/L. Concurrently, sediment magnetic properties were markedly enhanced around the well screen, pointing to neo-formed magnetite-like minerals. A reactive transport modeling approach was used to quantitatively evaluate the experimental observations and assess potential strategies for larger-scale implementation. The modeling results demonstrate that As removal was primarily achieved by adsorption onto neo-formed minerals and that an increased adsorption site density coincides with the finer-grained textures of the target aquifer. Up-scaled model simulations with 80-fold more Fe-nitrate reactants suggest that enough As-safe water can be produced to irrigate 1000 m2 of arid land for one season of water-intense rice cultivation at a low cost without causing undue contamination in surface soils that threatens agricultural sustainability.

Satellite observations reveal anthropogenic pressure significantly affects the suspended particulate matter concentrations in coastal waters of Hainan Island.

Suspended particulate matter (SPM) plays a crucial role in assessing the health status of coastal ecosystems. Satellite remote sensing offers an effective approach to investigate the variations and distribution patterns of SPM, with the performance of various satellite retrieval models exhibiting significant spatial heterogeneity. However, there is still limited information on precise remote sensing retrieval algorithms specifically designed for estimating SPM in tropical areas, hindering our ability to monitor the health status of valuable tropical ecological resources. A relatively accurate empirical algorithm (root mean square error = 2.241 mg L-1, mean absolute percentage error = 42.527%) was first developed for the coastal SPM of Hainan Island based on MODIS images and over a decade of field SPM data, which conducted comprehensive comparisons among empirical models, semi-analytical models, and machine learning models. Long-term monitoring from 2003 to 2022 revealed that the average SPM concentration along the coastal wetlands of Hainan Island was 6.848 mg L-1, which displayed a decreasing trend due to government environmental protection regulations (average rate of change of -0.009 mg L-1/year). The seasonal variations in coastal SPM were primarily influenced by sea surface temperature (SST). Spatially, the concentrations of SPM along the southwest coast of Hainan Island were higher in comparison to other waters, which was attributable to sediment types and ocean currents. Further, anthropogenic pressure (e.g., agricultural waste input, vegetation cover) was the main influence on the long-term changes of coastal SPM in Hainan Island, particularly evident in typical tropical ecosystems affected by aquaculture, coastal engineering, and changes in coastal green vegetation. Compared to other typical ecosystems around the globe, the overall health status of SPM along the coast wetlands of Hainan is considered satisfactory. These findings not only establish a robust remote sensing model for long-term SPM monitoring along the coast of Hainan Island, but also provide comprehensive insights into SPM dynamics, thereby contributing to the formulation of future coastal zone management policies.

Flexible SERS Biosensor Based on Core-Shell Nanotags for Sensitive and Multiple Detection of T1DM Biomarkers.

Sensitive and multiple detection of the biomarkers of type 1 diabetes mellitus (T1DM) is vital to the early diagnosis and clinical treatment of T1DM. Herein, we developed a SERS-based biosensor using polyvinylidene fluoride (PVDF) membranes as a flexible support for the detection of glutamic acid decarboxylase antibodies (GADA) and insulin autoantibodies (IAA). Two kinds of silver-gold core-shell nanotags embedded with Raman probes and attached with GADA or IAA antibodies were synthesized to capture the targets, enabling highly sensitive and highly selective detection of GADA and IAA. The embedded Raman probes sandwiched between silver and gold layers guaranteed spectral stability and reliability. Moreover, the utilization of two Raman probes enables simultaneous and multiplexing detection of both GADA and IAA, improving the detection accuracy for T1DM. The proposed SERS-based method has been proven feasible for clinical sample detection, demonstrating its great potential in sensitive, reliable, and rapid diagnosis of T1DM.

Chemotherapy-induced metastasis: molecular mechanisms and clinical therapies.

Chemotherapy, the most widely accepted treatment for malignant tumors, is dependent on cell death induced by various drugs including antimetabolites, alkylating agents, mitotic spindle inhibitors, antitumor antibiotics, and hormonal anticancer drugs. In addition to causing side effects due to non-selective cytotoxicity, chemotherapeutic drugs can initiate and promote metastasis, which greatly reduces their clinical efficacy. The knowledge of how they induce metastasis is essential for developing strategies that improve the outcomes of chemotherapy. Herein, we summarize the recent findings on chemotherapy-induced metastasis and discuss the underlying mechanisms including tumor-initiating cell expansion, the epithelial-mesenchymal transition, extracellular vesicle involvement, and tumor microenvironment alterations. In addition, the use of combination treatments to overcome chemotherapy-induced metastasis is also elaborated.

Advances in PD-1 signaling inhibition-based nano-delivery systems for tumor therapy.

In recent years, cancer immunotherapy has emerged as an exciting cancer treatment. Immune checkpoint blockade brings new opportunities for more researchers and clinicians. Programmed cell death receptor-1 (PD-1) is a widely studied immune checkpoint, and PD-1 blockade therapy has shown promising results in a variety of tumors, including melanoma, non-small cell lung cancer and renal cell carcinoma, which greatly improves patient overall survival and becomes a promising tool for the eradication of metastatic or inoperable tumors. However, low responsiveness and immune-related adverse effects currently limit its clinical application. Overcoming these difficulties is a major challenge to improve PD-1 blockade therapies. Nanomaterials have unique properties that enable targeted drug delivery, combination therapy through multidrug co-delivery strategies, and controlled drug release through sensitive bonds construction. In recent years, combining nanomaterials with PD-1 blockade therapy to construct novel single-drug-based or combination therapy-based nano-delivery systems has become an effective mean to address the limitations of PD-1 blockade therapy. In this study, the application of nanomaterial carriers in individual delivery of PD-1 inhibitors, combined delivery of PD-1 inhibitors and other immunomodulators, chemotherapeutic drugs, photothermal reagents were reviewed, which provides effective references for designing new PD-1 blockade therapeutic strategies.

Research on Kinematic and Static Filtering of the ESKF Based on INS/GNSS/UWB.

With the widespread development of multiple sensors for UGVs, the multi-source fusion-navigation system, which overcomes the limitations of the use of a single sensor, is becoming increasingly important in the field of autonomous navigation for UGVs. Because federated filtering is not independent between the filter-output quantities, owing to the use of the same state equation in each of the local sensors, a new kinematic and static multi-source fusion-filtering algorithm based on the error-state Kalman filter (ESKF) is proposed in this paper for the positioning-state estimation of UGVs. The algorithm is based on INS/GNSS/UWB multi-source sensors, and the ESKF replaces the traditional Kalman filter in kinematic and static filtering. After constructing the kinematic EKSF based on GNSS/INS and the static ESKF based on UWB/INS, the error-state vector solved by the kinematic ESKF was injected and set to zero. On this basis, the kinematic ESKF filter solution was used as the state vector of the static ESKF for the rest of the static filtering in a sequential form. Finally, the last static ESKF filtering solution was used as the integral filtering solution. Through mathematical simulations and comparative experiments, it is demonstrated that the proposed method converges quickly, and the positioning accuracy of the method was improved by 21.98% and 13.03% compared to the loosely coupled GNSS/INS and the loosely coupled UWB/INS navigation methods, respectively. Furthermore, as shown by the error-variation curves, the main performance of the proposed fusion-filtering method was largely influenced by the accuracy and robustness of the sensors in the kinematic ESKF. Furthermore, the algorithm proposed in this paper demonstrated good generalizability, plug-and-play, and robustness through comparative analysis experiments.

An Improved Magnetic Field Method to Locate the Grounding Conductor.

The location of the grounding grid conductors is critical for performing corrosion diagnosis and maintenance work. An improved magnetic field differential method to locate the unknown grounding grid based on truncation errors and the round-off errors analysis is presented in this paper. It was proven that a different order of the magnetic field derivative can be used to determine the position of the grounding conductor according to the peak value of the derivative. Due to the accumulative error of higher differentiation, the truncation error and rounding error were used to analyze to accumulative error and to determine the optimal step size to measure and calculate the higher differentiation. The possible range and probability distribution of the two kinds of errors at each order are described, and the index of peak position error was derived, which can be used to locate the grounding conductor in the power substation.

Fabrication and Properties of the Multifunctional Rapid Wound Healing Panax notoginseng@Ag Electrospun Fiber Membrane.

The Panax notoginseng@Ag core/shell electrospun fiber membrane was prepared by coaxial electrospinning combined with the UV reduction method (254 nm). The prepared Panax notoginseng@Ag core/shell nanofiber membrane has a three-dimensional structure, and its swelling ratio could reach as high as 199.87%. Traditional Chinese medicine Panax notoginseng can reduce inflammation, and the silver nanoparticles have antibacterial effects, which synergistically promote rapid wound healing. The developed Panax notoginseng@Ag core/shell nanofiber membrane can effectively inhibit the growth of the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus. The wound healing experiments in Sprague Dawley mice showed that the wound residual area rate of the Panax notoginseng@Ag core/shell electrospun nanofiber membrane group was only 1.52% on day 9, and the wound of this group basically healed on day 12, while the wound residual area rate of the gauze treatment group (control group) was 16.3% and 10.80% on day 9 and day 12, respectively. The wound of the Panax notoginseng@Ag core/shell electrospun nanofiber membrane group healed faster, which contributed to the application of the nanofiber as Chinese medicine rapid wound healing dressings.

Sand supplementation favors tropical seagrass Thalassia hemprichii in eutrophic bay: implications for seagrass restoration and management.

BACKGROUND: Sediment is crucial for the unique marine angiosperm seagrass growth and successful restoration. Sediment modification induced by eutrophication also exacerbates seagrass decline and reduces plantation and transplantation survival rates. However, we lack information regarding the influence of sediment on seagrass photosynthesis and the metabolics, especially regarding the key secondary metabolic flavone. Meanwhile, sulfation of flavonoids in seagrass may mitigate sulfide intrusion, but limited evidence is available. RESULTS: We cultured the seagrass Thalassia hemprichii under controlled laboratory conditions in three sediment types by combining different ratios of in-situ eutrophic sediment and coarse beach sand. We examined the effects of beach sand mixed with natural eutrophic sediments on seagrass using photobiology, metabolomics and isotope labelling approaches. Seagrasses grown in eutrophic sediments mixed with beach sand exhibited significantly higher photosynthetic activity, with a larger relative maximum electron transport rate and minimum saturating irradiance. Simultaneously, considerably greater belowground amino acid and flavonoid concentrations were observed to counteract anoxic stress in eutrophic sediments without mixed beach sand. This led to more positive belowground stable sulfur isotope ratios in eutrophic sediments with a lower Eh. CONCLUSIONS: These results indicated that coarse beach sand indirectly enhanced photosynthesis in T. hemprichii by reducing sulfide intrusion with lower amino acid and flavonoid concentrations. This could explain why T. hemprichii often grows better on coarse sand substrates. Therefore, it is imperative to consider adding beach sand to sediments to improve the environmental conditions for seagrass and restore seagrass in eutrophic ecosystems.

BIRC5 regulates inflammatory tumor microenvironment-induced aggravation of penile cancer development in vitro and in vivo.

BACKGROUND: Baculoviral IAP repeat containing 5 (BIRC5) is overexpressed and plays as a key regulator in the progression of various human carcinomas. The inflammatory tumor microenvironment (ITM) is closely associated with the development of cancers. However, the role of BIRC5 in penile cancer (PC) and the ITM-induced abnormal progression of PC is still obscure. METHODS: In this study, serum and tissues of patients with PC were recruited to evaluate the expression profile of BIRC5. We used PC cell lines (Penl1 and Penl2) and constructed a PC xenograft mice model to explore the effects of the silencing of BIRC5 on proliferation, migration, invasion and tumor growth, as well as survival of mice. Besides, interferon (IFN)-γ was utilized to mimic the ITM of PC cells. RESULTS: Our results showed that BIRC5 was dramatically upregulated in the serum and tissues of PC patients, as well as PC cell lines. Knockdown of BIRC5 inhibited the proliferation, migration and invasion of PC cells. Meanwhile, it suppressed PC xenograft tumor growth and improved mice survival. Moreover, IFN-γ significantly aggravated PC progression both in vivo and in vitro while the silencing of BIRC5 reversed these unfavorable effects. CONCLUSIONS: Taken together, our data revealed that BIRC5 silencing inhibited aggravation of PC cell processes and tumor development induced by ITM. This suggested that BIRC5 may function as a diagnosis and therapy target of PC in the future.

Current Methods and Prospects for Analysis and Characterization of Nanomaterials in the Environment.

Analysis and characterization of naturally occurring and engineered nanomaterials in the environment are critical for understanding their environmental behaviors and defining real exposure scenarios for environmental risk assessment. However, this is challenging primarily due to the low concentration, structural heterogeneity, and dynamic transformation of nanomaterials in complex environmental matrices. In this critical review, we first summarize sample pretreatment methods developed for separation and preconcentration of nanomaterials from environmental samples, including natural waters, wastewater, soils, sediments, and biological media. Then, we review the state-of-the-art microscopic, spectroscopic, mass spectrometric, electrochemical, and size-fractionation methods for determination of mass and number abundance, as well as the morphological, compositional, and structural properties of nanomaterials, with discussion on their advantages and limitations. Despite recent advances in detecting and characterizing nanomaterials in the environment, challenges remain to improve the analytical sensitivity and resolution and to expand the method applications. It is important to develop methods for simultaneous determination of multifaceted nanomaterial properties for in situ analysis and characterization of nanomaterials under dynamic environmental conditions and for detection of nanoscale contaminants of emerging concern (e.g., nanoplastics and biological nanoparticles), which will greatly facilitate the standardization of nanomaterial analysis and characterization methods for environmental samples.

Nutrient loading decreases blue carbon by mediating fungi activities within seagrass meadows.

Coastal pollution, including nutrient loading, can negatively impact seagrass health and cover and may consequently alter soil organic carbon (SOC) accumulation and preservation. Key to understanding how eutrophication impacts SOC cycling in seagrass ecosystems is how nutrient loading changes the sources of carbon being deposited and how these changes in resources, both nutrients and carbon availability, influence soil microbiota community and activity. Currently, the direction and magnitude of nutrient loading impacts on seagrass SOC dynamics are poorly understood at a meadow scale, limiting our ability to reveal the driving mechanisms of SOC remineralisation. The purpose of this study was to assess the response of surface SOC and soil microbiomes to nutrient loading within tropical seagrass meadows. To achieve this, we quantified both total SOC and recalcitrant soil organic carbon (RSOC) concentrations and sources, in addition to the composition of bacterial and fungal communities and soil extracellular enzyme activities. We found that nutrient loading elevated SOC and RSOC content, mainly facilitated by enhanced algal growth. There was no nutrient effect on the soil prokaryotic communities, however, saprotrophic fungi groups (i.e. Trapeliales, Sordaridales, Saccharomycetales and Polyporales) and fungal activities were elevated under high nutrient conditions, including extracellular enzyme activities linked to seagrass-based cellulose and lignin decomposition. This relative increase in RSOC transformation may decrease the relative contribution of seagrass carbon to RSOC pools. Additionally, significantly different fungal communities were observed between adjacent T. hemprichii and E. acoroides areas, which coincided with elevated RSOC-decomposing enzyme activity in T. hemprichii meadows, even though the mixed seagrass meadow received allochthonous SOC and RSOC from the same sources. These results suggest that nutrient loading stimulated fungal activity and community shifts specific to the local seagrass species, thereby causing fine-scale (within-meadow) variability in SOC cycling in response to nutrient loading. This study provides evidence that fungal composition and activity, mediated by human activities (e.g. nutrient loading), can be an important influence on seagrass blue carbon accumulation and remineralisation.

Research on UAV Robust Adaptive Positioning Algorithm Based on IMU/GNSS/VO in Complex Scenes.

As an important component of autonomous intelligent systems, the research on autonomous positioning algorithms used by UAVs is of great significance. In order to resolve the problem whereby the GNSS signal is interrupted, and the visual sensor lacks sufficient feature points in complex scenes, which leads to difficulties in autonomous positioning, this paper proposes a new robust adaptive positioning algorithm that ensures the robustness and accuracy of autonomous navigation and positioning in UAVs. On the basis of the combined navigation model of vision/inertial navigation and satellite/inertial navigation, based on ESKF, a multi-source fusion model based on a federated Kalman filter is here established. Furthermore, a robust adaptive localization algorithm is proposed, which uses robust equivalent weights to estimate the sub-filters, and then uses the sub-filter state covariance to adaptively assign information sharing coefficients. After simulation experiments and dataset verification, the results show that the robust adaptive algorithm can effectively limit the impact of gross errors in observations and mathematical model deviations and can automatically update the information sharing coefficient online according to the sub-filter equivalent state covariance. Compared with the classical federated Kalman algorithm and the adaptive federated Kalman algorithm, our algorithm can meet the real-time requirements of navigation, and the accuracy of position, velocity, and attitude measurement is improved by 2-3 times. The robust adaptive localization algorithm proposed in this paper can effectively improve the reliability and accuracy of autonomous navigation systems in complex scenes. Moreover, the algorithm is general-it is not intended for a specific scene or a specific sensor combination- and is applicable to individual scenes with varied sensor combinations.

UAV Localization Algorithm Based on Factor Graph Optimization in Complex Scenes.

With the increasingly widespread application of UAV intelligence, the need for autonomous navigation and positioning is becoming more and more important. To solve the problem that UAV cannot perform localization in complex scenes, a new multi-source fusion framework factor graph optimization algorithm is used for UAV localization state estimation in this paper, which is based on IMU/GNSS/VO multi-source sensors. Based on the factor graph model and the iSAM incremental inference algorithm, a multi-source fusion model of IMU/GNSS/VO is established, including the IMU pre-integration factor, IMU bias factor, GNSS factor, and VO factor. Mathematical simulations and validations on the EuRoC dataset show that, when the selected sliding window size is 30, the factor graph optimization (FGO) algorithm can not only meet the requirements of real time and accuracy at the same time, but it also achieves a plug-and-play function in the event of local sensor failures. Finally, compared with the traditional federated Kalman algorithm and the adaptive federated Kalman algorithm, the positioning accuracy of the FGO algorithm in this paper is improved by 1.5-2-fold, and can effectively improve autonomous navigation system robustness and flexibility in complex scenarios. Moreover, the multi-source fusion framework in this paper is a general algorithm framework that can satisfy other scenarios and other types of sensor combinations.

Metformin Hydrochloride Mucosal Nanoparticles-Based Enteric Capsule for Prolonged Intestinal Residence Time, Improved Bioavailability, and Hypoglycemic Effect.

Metformin hydrochloride enteric-coated capsule (MH-EC) is a commonly used clinical drug for the treatment of type 2 diabetes. In this study, we described a metformin hydrochloride mucosal nanoparticles enteric-coated capsule (MH-MNPs-EC) based on metformin hydrochloride chitosan mucosal nanoparticles (MH-CS MNPs) and its preparation method to improve the bioavailability and hypoglycemic effect duration of MH-EC. In intestinal adhesion study, the residue rates of free drugs and mucosal nanoparticles were 10.52% and 67.27%, respectively after cleaned with PBS buffer. MH-CS MNPs could significantly improve the efficacy of MH and promote the rehabilitation of diabetes rats. In vitro release test of MH-MNPs-EC showed continuous release over 12 h, while commercial MH-EC released completely within about 1 h in intestinal environment (pH 6.8). Pharmacokinetic study was performed in beagle dogs compared to the commercial MH-EC. The durations of blood MH concentration above 2 µg/mL were 9 h for MH-MNPs-EC versus 2 h for commercial MH-EC. The relative bioavailability of MH-MNPs-EC was determined as 185.28%, compared with commercial MH-EC. In conclusion, MH-CS MNPs have good intestinal adhesion and can significantly prolong the residence time of MH in the intestine. MH-MNPs-EC has better treatment effect compared with MH-EC, and it is expected to be a potential drug product for the treatment of diabetes because of its desired characteristics.

[Antibiotic use in very low birth weight/extremely low birth weight infants in 15 hospitals in Jiangsu Province of China: a multicenter survey]. / 江苏省15家医院极低/è¶ ä½Žå‡ºç”Ÿä½“é‡å„¿æŠ—ç”Ÿç´ ä½¿ç”¨çŽ°çŠ¶è°ƒæŸ¥.

OBJECTIVES: To investigate the current status of antibiotic use in very low birth weight/extremely low birth weight infants in Jiangsu Province of China, and to provide a clinical basis for the quality and improvement of antibiotic management in the neonatal intensive care unit (NICU). METHODS: A retrospective analysis was performed on the data on general conditions and antibiotic use in the very low birth weight/extremely low birth weight infants who were admitted to 15 hospitals of Jiangsu Province from January 1, 2019 to December 31, 2020. A questionnaire containing 10 measures to reduce antibiotic use was designed to investigate the implementation of these intervention measures. RESULTS: A total of 1 920 very low birth weight/extremely low birth weight infants were enrolled, among whom 1 846 (96.15%) were treated with antibiotic, and the median antibiotic use rate (AUR) was 50/100 patient-days. The AUR ranged from 24/100 to 100/100 patient-days in the 15 hospitals. After adjustment for the confounding factors including gestational age, birth weight, and neonatal critical score, the Poisson regression analysis showed that there was a significant difference in the adjusted AUR (aAUR) among the hospitals (P<0.01). The investigation results showed that among the 10 measures to reduce antibiotic use, 8 measures were implemented in less than 50% of these hospitals, and the number of intervention measures implemented was negatively correlated with aAUR (rs=-0.564, P=0.029). CONCLUSIONS: There is a high AUR among the very low birth weight/extremely low birth weight infants in the 15 hospitals of Jiangsu Province, with a significant difference among hospitals. The hospitals implementing a relatively few measures to reduce antibiotic use tend to have a high AUR. It is expected to reduce AUR in very low birth weight/extremely low birth weight infants by promoting the quality improvement of antibiotic use management in the NICU.

Clinical effect of different maintenance doses of caffeine citrate in the treatment of preterm infants requiring assisted ventilation: a pilot multicenter study. / ä¸åŒç»´æŒå‰‚é‡æž¸æ©¼é ¸å’–å•¡å› å¯¹è¾ åŠ©é€šæ°”æ—©äº§å„¿çš„ç–—æ•ˆè¯„ä¼°ï¼šä¸€é¡¹åˆæ­¥å¤šä¸­å¿ƒç ”ç©¶.

OBJECTIVES: To explore the optimal maintenance dose of caffeine citrate for preterm infants requiring assisted ventilation and caffeine citrate treatment. METHODS: A retrospective analysis was performed on the medical data of 566 preterm infants (gestational age ≤34 weeks) who were treated and required assisted ventilation and caffeine citrate treatment in the neonatal intensive care unit of 30 tertiary hospitals in Jiangsu Province of China between January 1 and December 31, 2019. The 405 preterm infants receiving high-dose (10 mg/kg per day) caffeine citrate after a loading dose of 20 mg/kg within 24 hours after birth were enrolled as the high-dose group. The 161 preterm infants receiving low-dose (5 mg/kg per day) caffeine citrate were enrolled as the low-dose group. RESULTS: Compared with the low-dose group, the high-dose group had significant reductions in the need for high-concentration oxygen during assisted ventilation (P=0.044), the duration of oxygen inhalation after weaning from noninvasive ventilation (P<0.01), total oxygen inhalation time during hospitalization (P<0.01), the proportion of preterm infants requiring noninvasive ventilation again (P<0.01), the rate of use of pulmonary surfactant and budesonide (P<0.05), and the incidence rates of apnea and bronchopulmonary dysplasia (P<0.01), but the high-dose group had a significantly increased incidence rate of feeding intolerance (P=0.032). There were no significant differences between the two groups in the body weight change, the incidence rates of retinopathy of prematurity, intraventricular hemorrhage or necrotizing enterocolitis, the mortality rate, and the duration of caffeine use (P>0.05). CONCLUSIONS: This pilot multicenter study shows that the high maintenance dose (10 mg/kg per day) is generally beneficial to preterm infants in China and does not increase the incidence rate of common adverse reactions. For the risk of feeding intolerance, further research is needed to eliminate the interference of confounding factors as far as possible.

Macroalgal Blooms Trigger the Breakdown of Seagrass Blue Carbon.

Intensive macroalgal blooms, a source of labile organic carbon (LOC) induced by coastal nutrient loading in some seagrass ecosystems, create ideal conditions for enhanced recalcitrant organic carbon (ROC) loss via the cometabolism effect. Here, we carried out a 62-day laboratory experiment to see if density-dependent addition of macroalgal biomass can influence the seagrass decomposition process, including seagrass detritus carbon chemistry, greenhouse emissions, and bacterial communities. We found that higher density macroalgal addition stimulated microbes to decompose ∼20% more of the seagrass biomass compared to other treatments, which was also reflected in enhanced (∼twofold) greenhouse gas emissions. Although the composition of the seagrass-associated microbiome communities was unaffected by the addition of macroalgae, we showed that high macroalgal addition caused a relative depletion in the ROC as lignin and lipid compounds, as well as δ13C depletion and δ15N enrichment of the seagrass detritus. These results suggest that macroalgal blooms may stimulate the remineralization of recalcitrant components of seagrass detritus via cometabolism, possibly through providing available energy or resources for the synthesis of ROC-degrading enzymes within the resident microbial population. This study provides evidence that cometabolism can be a mechanism for leading to reduced seagrass blue carbon sequestration and preservation.

Rapid environmental change shapes pond water microbial community structure and function, affecting mud crab (Scylla paramamosain) survivability.

The aquatic microbial community is sensitive to environmental change; however, the impacts of those changes combined with disease outbreaks affecting S. paramamosain are unknown. Thus, from March to October, we explored the interaction between aquacultural environmental conditions and microbial composition and function in open-air aquaculture ponds containing S. paramamosain in Southern China. The microbial community structure was significantly positively correlated with microbial community function. The environment variables such as temperature and salinity during May and June changed more quickly compared with other periods, resulting changes in the structure and function of the microbial community affected S. paramamosain survivability, with higher crab mortality observed from May to June compared with other periods. These included changes in the relative abundance of Microtrichales, Synechococcales, Rhodobacterales, Chitinophagales, and SAR11_clade, and corresponding functions associated with glycolysis and/or gluconeogenesis, porphyrin and chlorophyll metabolism, photosynthetic proteins, and transcription factors. These changes could impact S. paramamosain mortality and be used to evaluate the health status of the ponds. Though the environment variables during July~October changed slowly comparing to May and June, the ponds microflora changed which benefit S. paramamosain survivability with correspondingly low S. paramamosain mortality. Therefore, rapid environmental change alters the structure and function of the aquatic microflora, increasing S. paramamosain mortality.