Facile and efficient transformation of thiols to disulfides via a radical pathway with N-anomeric amide.

Radical coupling of thiols is an attractive route for the synthesis of disulfides, but this approach should be promoted by strong oxidants and/or metal salts in combination with additives, which limits its substrate scope and application. In this work, the N-anomeric amide was first found to be able to realize the conversion of thiols to sulfur radicals with high efficiency in the absence of an oxidant or any additives for the synthesis of symmetrical disulfides. The protocol features mild reaction conditions, good functional group tolerance, and moderate to excellent yields.

Transcriptome Analysis of mfs2-Defective Penicillium digitatum Mutant to Reveal Importance of Pdmfs2 in Developing Fungal Prochloraz Resistance.

Demethylation inhibitors (DMIs), including prochloraz, are popular fungicides to control citrus postharvest pathogens such as Penicillium digitatum (green mold). However, many P. digitatum strains have developed prochloraz resistance, which decreases drug efficacy. Specific major facilitator superfamily (MFS) transporter gene mfs2, encoding drug-efflux pump protein MFS2, has been identified in P. digitatum strain F6 (PdF6) to confer fungal strain prochloraz resistance. However, except for the drug-efflux pump function of MFS2, other mechanisms relating to the Pdmfs2 are not fully clear. The present study reported a transcriptome investigation on the mfs2-defective P. digitatum strain. Comparing to the wild-type strain, the mfs2-defective strain showed 717 differentially expressed genes (DEGs) without prochloraz induction, and 1221 DEGs with prochloraz induction. The obtained DEGs included multiple isoforms of MFS transporter-encoding genes, ATP-binding cassette (ABC) transporter-encoding genes, and multidrug and toxic compound extrusion (MATE) family protein-encoding genes. Many of these putative drug-efflux pump protein-encoding genes had significantly lower transcript abundances in the mfs2-defective P. digitatum strain at prochloraz induction, as compared to the wild-type strain, including twenty-two MFS transporter-encoding genes (MFS1 to MFS22), two ABC transporter-encoding genes (ABC1 and ABC2), and three MATE protein-encoding genes (MATE1 to MATE3). The prochloraz induction on special drug-efflux pump protein genes in the wild-type strain was not observed in the mfs2-defective strain, including MFS21, MFS22, ABC2, MATE1, MATE2, and MATE3. On the other hand, the up-regulation of other drug-efflux pump protein genes in the mfs2-defective strain cannot recover the fungal prochloraz resistance, including MFS23, MFS26, MFS27, MFS31, MFS33, and ABC3 to ABC8. The functional enrichment of DEGs based on Kyoto Encyclopedia of Genes and Genomes (KEGG), Clusters of Orthologous Groups (COG), and euKaryotic Orthologous Groups (KOG) database resources suggested some essential contributors to the mfs2-relating prochloraz resistance, including ribosome biosynthesis-related genes, oxidative phosphorylation genes, steroid biosynthesis-related genes, fatty acid and lipid metabolism-related genes, and carbon- and nitrogen-metabolism-related genes. The results indicated that the MFS2 transporter might be involved in the regulation of multiple drug-efflux pump protein gene expressions and multiple metabolism-related gene expressions, thus playing an important role in developing P. digitatum prochloraz resistance.

Suberoylanilide hydroxamic acid attenuates cognitive impairment in offspring caused by maternal surgery during mid-pregnancy.

Some pregnant women have to experience non-obstetric surgery during pregnancy under general anesthesia. Our previous studies showed that maternal exposure to sevoflurane, isoflurane, propofol, and ketamine causes cognitive deficits in offspring. Histone acetylation has been implicated in synaptic plasticity. Propofol is commonly used in non-obstetric procedures on pregnant women. Previous studies in our laboratory showed that maternal propofol exposure in pregnancy impairs learning and memory in offspring by disturbing histone acetylation. The present study aims to investigate whether HDAC inhibitor suberoylanilide hydroxamic acid (SAHA) could attenuate learning and memory deficits in offspring caused by maternal surgery under propofol anesthesia during mid-pregnancy. Maternal rats were exposed to propofol or underwent abdominal surgery under propofol anesthesia during middle pregnancy. The learning and memory abilities of the offspring rats were assessed using the Morris water maze (MWM) test. The protein levels of histone deacetylase 2 (HDAC2), phosphorylated cAMP response-element binding (p-CREB), brain-derived neurotrophic factor (BDNF), and phosphorylated tyrosine kinase B (p-TrkB) in the hippocampus of the offspring rats were evaluated by immunofluorescence staining and western blot. Hippocampal neuroapoptosis was detected by TUNEL staining. Our results showed that maternal propofol exposure during middle pregnancy impaired the water-maze learning and memory of the offspring rats, increased the protein level of HDAC2 and reduced the protein levels of p-CREB, BDNF and p-TrkB in the hippocampus of the offspring, and such effects were exacerbated by surgery. SAHA alleviated the cognitive dysfunction and rescued the changes in the protein levels of p-CREB, BDNF and p-TrkB induced by maternal propofol exposure alone or maternal propofol exposure plus surgery. Therefore, SAHA could be a potential and promising agent for treating the learning and memory deficits in offspring caused by maternal nonobstetric surgery under propofol anesthesia.

Satellite observations of suspended particulate matter concentration in Lake Gaoyou in the past four decades.

Suspended Particulate Matter (SPM) concentration stands as a pivotal determinant of water quality within lake ecosystems. However, comprehension of the enduring dynamics of SPM within lakes is severely hindered due to a shortage of long-term records. Our research has developed a robust remote sensing algorithm to retrieve the SPM concentration in Lake Gaoyou, situated in the lower reaches of the Huai River basin in China. The algorithm demonstrates commendable performance, with an uncertainty of 28.68 %. Leveraging Landsat series sensors imagery, our investigation yields high spatial resolution SPM concentration maps, which first provide a four-decades record of the SPM distribution within Lake Gaoyou. Our findings unveil a significant annual reduction of 1.35 mg L-1 in SPM concentration over the past four decades. This notable decline is probably attributable to a series of ecological initiatives to enhancing the management of the eco-friendly within the basin. Furthermore, our research delineated the influence of environmental factors on the intra-annual SPM dynamics across distinct spatial domains, encompassing the natural inlet region, semi-obstructed inlet region and outlet areas within the lake The SPM concentration in the natural inlet region exhibits a conspicuous correlation with precipitation. Increased precipitation induces runoff within the basin, facilitating the transport of suspended solids and sediment into the lake, consequently augmenting SPM levels. Conversely, the semi-obstructed inlet and outlet areas are predominantly influenced by the wind field, with variations in SPM attributed to sediment resuspension caused by water mixing driven by wind forcing. Our research can be considered an important reference to the evaluation of the management of the lake over long periods.

Abdominal surgery under ketamine anesthesia during second trimester impairs hippocampal learning and memory of offspring by regulating dendrite spine remodeling in rats.

Recent evidence showed that general anesthesia produces long-term neurotoxicity and cognitive dysfunction. However, it remains unclear whether maternal non-obstetric surgery under ketamine anesthesia during second trimester causes cognitive impairment in offspring. The present study assigned pregnant rats into three groups: 1) normal control group receiving no anesthesia and no surgery, 2) ketamine group receiving ketamine anesthesia for 2 h on the 14th day of gestation but no surgery, and 3) surgery group receiving abdominal surgery under ketamine anesthesia on the 14th day of gestation. On postnatal day 1, the offspring rats in Ketamine group and surgery group were assigned to receive intra-peritoneal injection of Senegenin (15 mg/kg), once per day for consecutive 14 days. The offspring's spatial perception, anxiety-like behavior, and learning and memory were evaluated. Then the offspring's hippocampal tissues were collected. The offspring of the surgery group were impaired in the spatial perception in the cliff avoidance test and the spatial learning and memory in the Morris water maze test. Accordingly, the activity of histone deacetylases increased, the protein levels of NEDD9, BDNF, p-TrkB, Syn and PSD-95 decreased, and the density of dendritic spines reduced in the hippocampus of the offspring of the surgery group, and such effects were not seen in the offspring of the ketamine group, neither in the offspring of control group. Senegenin alleviated the learning and memory impairment, and increased the protein levels of NEDD9, BDNF, p-TrkB, Syn and PSD-95 and the density of dendritic spines in the offspring of the surgery group. ketamine anesthesia plus surgery during second trimester impairs hippocampus-dependent learning and memory, and the deficits could be rescued by treatment with Senegenin.

Estimating four-decadal variations of seagrass distribution using satellite data and deep learning methods in a marine lagoon.

Seagrasses are marine flowering plants that inhabit shallow coastal and estuarine waters and serve vital ecological functions in marine ecosystems. However, seagrass ecosystems face the looming threat of degradation, necessitating effective monitoring. Remote-sensing technology offers significant advantages in terms of spatial coverage and temporal accessibility. Although some remote sensing approaches, such as water column correction, spectral index-based, and machine learning-based methods, have been proposed for seagrass detection, their performances are not always satisfactory. Deep learning models, known for their powerful learning and vast data processing capabilities, have been widely employed in automatic target detection. In this study, a typical seagrass habitat (Swan Lake) in northern China was used to propose a deep learning-based model for seagrass detection from Landsat satellite data. The performances of UNet and SegNet at different patch scales for seagrass detection were compared. The results showed that the SegNet model at a patch scale of 16 × 16 pixels worked well, with validation accuracy and loss of 96.3 % and 0.15, respectively, during training. Evaluations based on the test dataset also indicated good performance of this model, with an overall accuracy >95 %. Subsequently, the deep learning model was applied for seagrass detection in Swan Lake between 1984 and 2022. We observed a noticeable seasonal variation in germination, growth, maturation, and shrinkage from spring to winter. The seagrass area decreased over the past four decades, punctuated by intermittent fluctuations likely attributed to anthropogenic activities, such as aquaculture and construction development. Additionally, changes in landscape ecology indicators have demonstrated that seagrass experiences severe patchiness. However, these problems have weakened recently. Overall, by combining remote sensing big data with deep learning technology, our study provides a valuable approach for the highly precise monitoring of seagrass. These findings on seagrass area variation in Swan Lake offer significant information for seagrass restoration and management.

Altered Brain Function in Pediatric Patients With Complete Spinal Cord Injury: A Resting-State Functional MRI Study.

BACKGROUND: Injury to the spinal cord of children may cause potential brain reorganizations, affecting their rehabilitation. However, the specific functional alterations of children after complete spinal cord injury (CSCI) remain unclear. PURPOSE: To explore the specific functional changes in local brain and the relationship with clinical characteristics in pediatric CSCI patients, clarifying the impact of CSCI on brain function in developing children. STUDY TYPE: Prospective. SUBJECTS: Thirty pediatric CSCI patients (7.83 ± 1.206 years) and 30 age-, gender-matched healthy children as controls (HCs) (8.77 ± 2.079 years). FIELD STRENGTH/SEQUENCE: 3.0 T/Resting-state functional MRI (rs-fMRI) using echo-planar-imaging (EPI) sequence. ASSESSMENT: Amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) were used to characterize regional neural function. STATISTICAL TESTS: Two-sample t-tests were used to compare the ALFF, fALFF, ReHo values of the brain between pediatric CSCI and HCs (voxel-level FWE correction, P < 0.05). Spearman correlation analyses were performed to analyze the associations between the ALFF, fALFF, ReHo values in altered regions and the injury duration, sensory motor scores of pediatric CSCI patients (P < 0.05). Then receiver operating characteristic (ROC) analysis was conducted to identify possible sensitive imaging indicators for clinical therapy. RESULTS: Compared with HCs, pediatric CSCI showed significantly decreased ALFF in the right postcentral gyrus (S1), orbitofrontal cortex, and left superior temporal gyrus (STG), increased ALFF in bilateral caudate nucleus, thalamus, middle cingulate gyrus, and cerebellar lobules IV-VI, and increased ReHo in left cerebellum Crus II and Brodmann area 21. The ALFF value in the right S1 negatively correlated with the pinprick and light touch sensory scores of pediatric CSCI. When the left STG was used as an imaging biomarker for pediatric CSCI, it achieved the highest area under the curve of 0.989. CONCLUSIONS: These findings may provide potential neural mechanisms for sensory motor and cognitive-emotional deficits in children after CSCI. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 5.

Remote sensing detection of seagrass distribution in a marine lagoon (Swan Lake), China.

Seagrass, a submerged flowering plant, is widely distributed in coastal shallow waters and plays a significant role in maintaining marine biodiversity and carbon cycles. However, the seagrass ecosystem is currently facing degradation, necessitating effective monitoring. Satellite remote sensing observations offer distinct advantages in spatial coverage and temporal frequency. In this study, we focused on a marine lagoon (Swan Lake), located in the Shandong Peninsula of China which is characterized by a large and typical seagrass population. We conducted an analysis of remote sensing reflectance of seagrass and other objectives using a comprehensive Landsat satellite dataset spanning from 2002 to 2022. Subsequently, we constructed Seagrass Index I (SSI-I) and Seagrass Index II (SSI-II), and used them to develop a stepwise model for seagrass detection from Landsat images. Validation was performed using in situ acoustic survey data and visual interpretation, revealing the good performance of our model with an overall accuracy exceeding 0.90 and a kappa coefficient around 0.80. The long-term analysis (2002-2022) of the seagrass distribution area in Swan Lake, generated from Landsat data using our model, indicated that the central area of Swan Lake sustains seagrass for the longest duration. Seagrass in Swan Lake exhibits a regular seasonal variation, including seeding in early spring, growth in spring-summer, maturation in the middle of summer, and shrinkage in autumn. Furthermore, we observed an overall decreasing trend in the seagrass area over the past 20 years, while occasional periods of seagrass restoration were also observed. These findings provide crucial information for seagrass protection, marine blue carbon studies, and related endeavors in Swan Lake. Moreover, our study offers a valuable alternative approach that can be implemented for seagrass monitoring using satellite observations in other coastal regions.

A global satellite observation of phytoplankton taxonomic groups over the past two decades.

Marine phytoplankton fuel the oceanic biotic chain, determine the carbon sequestration levels, and are crucial for the global carbon cycle and climate change. In the present study, we show a near-two-decadal (2002-2022) spatiotemporal distribution of global phytoplankton abundance, proxy as dominant phytoplankton taxonomic groups (PTGs), with a newly developed remote sensing model. Globally, six chief PTGs, namely chlorophytes (~26%), diatoms (~24%), haptophytes (~15%), cryptophytes (~10%), cyanobacteria (~8%), and dinoflagellates (~3%), explain most of the variation (~86%) in phytoplankton assemblages. Spatially, diatoms generally dominate high latitudes, marginal seas, and coastal upwelling zones, whereas chlorophytes and haptophytes control the open oceans. Satellite observations reveal a gentle multi-annual trend of the PTGs in the major oceans, indicative of roughly "unchanged" conditions on the total biomass or compositions of the phytoplankton community. Jointly, "changed" status applies to a short-term (seasonal) timescale: (1) Fluctuations of PTGs exhibit different amplitudes among different subregions, together with a general rule-more intense vibration in the Northern Hemisphere and polar oceans than other zones; (2) diatoms and haptophytes vary more dramatically than other PTGs in a global-scale scope. These findings provide a clear picture of the global phytoplankton community composition and can improve our understanding of their state and further analysis of marine biological processes.

A multiple-step screening protocol to identify norepinephrine and dopamine reuptake inhibitors for depression.

Depression severely impairs the health of people all over the world. Cognitive dysfunction due to depression has resulted in a severe economic burden to family and society induced by the reduction of social functioning of patients. Norepinephrine-dopamine reuptake inhibitors (NDRIs) targeted with the human norepinephrine transporter (hNET) and distributed with the human dopamine transporter (hDAT) simultaneously treat depression and improve cognitive function, and they effectively prevent sexual dysfunction and other side effects. Because many patients continue to poorly respond to NDRIs, it is urgent to discover novel NDRI antidepressants that do not interfere with cognitive function. The aim of this work was to selectively identify novel NDRI candidates acting against hNET and hDAT from large compound libraries by a comprehensive strategy integrating support vector machine (SVM) models, ADMET, molecular docking, in vitro binding assays, molecular dynamics simulation, and binding energy calculation. First, 6522 compounds that do not inhibit the human serotonin transporter (hSERT) were obtained by SVM models of hNET, hDAT, and non-target hSERT with similarity analyses from compound libraries. ADMET and molecular docking were then used to identify compounds that could potently bind to the hNET and hDAT with satisfactory ADMET, and 4 compounds were successfully identified. According to their docking scores and ADMET information, 3719810 was advanced for profiling by in vitro assays as a novel NDRI lead compound due to its strongest druggability and balancing activities. Encouragingly, 3719810 performed comparative activities on two targets, with Ki values of 7.32 µM for hNET and 5.23 µM for hDAT. To obtain candidates with additional activities and balance the activities of 2 targets, 5 analogs were optimized, and 2 novel scaffold compounds were successively designed. By assessment of molecular docking, molecular dynamics simulations, and binding energy calculations, 5 compounds were validated as NDRI candidates with high activities, and 4 of them performed acceptable balancing activities acting on hNET and hDAT. This work supplied promising novel NDRIs for treatment of depression with cognitive dysfunction or other related neurodegenerative disorders, and also provided a strategy for highly efficient and cost-effective identification of inhibitors for dual targets with homologous non-targets.

Satellite estimation of suspended particle types using a backscattering efficiency-based model in the marginal seas.

The particle composition of suspended matter provides crucial information for a deeper understanding of marine biogeochemical processes and environmental changes. Particulate backscattering efficiency (Qbbe(λ)) is critical to understand particle composition, and a Qbbe(λ)-based model for classifying particle types was proposed. In this study, we evaluated the applicability of the Qbbe(λ)-based model to satellite observations in the shallow marginal Bohai and Yellow Seas. Spatiotemporal variations of the particle types and their potential driving factors were studied. The results showed that the Qbbe(λ) products generated from Moderate Resolution Imaging Spectroradiometer (MODIS) on the satellite Aqua agreed well with the in situ measured values, with determination coefficient, root mean square error, bias, and mean absolute percentage error of 0.76, 0.007, 16.5%, and 31.0%, respectively. This result verifies the satellite applicability of the Qbbe(λ)-based model. Based on long-term MODIS data, we observed evident spatiotemporal variations of the Qbbe(λ), from which distinct particle types were identified. Coastal waters were often dominated by minerals, with high Qbbe(λ) values, though their temporal changes were also observed. In contrast, waters in the offshore regions showed clear changes in particle types, which shifted from organic-dominated with low Qbbe(λ) levels in summer to mineral-dominated with high Qbbe(λ) values in winter. We also observed long-term increasing and decreasing trends in Qbbe(λ) in some regions, indicating a relative increase in the proportions of mineral and organic particles in the past decades, respectively. These spatiotemporal variations of Qbbe(λ) and particle types were probably attributed to sediment re-suspension related to water mixing driven by wind and tidal forcing, and to sediment load associated with river discharge. Overall, the findings of this study may provide valuable proxies for better studying marine biogeochemical processes, material exchanges, and sediment flux.

Bronchogenic cysts with infection in the chest wall skin of a 64-year-old asymptomatic patient: A case report.

BACKGROUND: Skin bronchogenic cysts are extremely rare congenital bronchocystic changes caused by the abnormal development of the trachea, bronchial trees or lung buds during the embryonic period. The first case of skin bronchogenic cysts was reported in 1945. Since then, this disease has attracted increasing attention, but due to the low incidence, its pathogenesis is still not clear. CASE SUMMARY: Here, we report another case of skin bronchogenic cysts with infection in a 64-year-old female patient. The patient had no symptoms for more than 60 years until her chest wall was recently found to be swollen, and she felt pain and discomfort. At the same time, secretions were found on the surface of the swelling. Color Doppler ultrasound examination showed abnormal echoes in the soft tissue under the frontal chest wall, suggesting the presence of cysts. Cytological puncture resulted in about 2 mL of pus and showed the presence of more acute inflammatory cells. The final clinical diagnosis was skin cyst with infection, and surgery was carried out. The pathological results obtained after surgery showed that the cystic wall was covered with column-like cilia epithelial cells, and the interstitial structure was partially inundated with inflammatory cells. After a variety of examinations and clinical diagnoses, we finally confirmed that the patient was suffering from bronchogenic cyst. CONCLUSION: This article not only describes the case of an elderly patient with rare skin bronchogenic cysts with infection but also provides a detailed and correct diagnosis and a successful treatment process, which is of great value for the diagnosis and treatment of the disease.

Long-term spatial variation of algal blooms extracted using the U-net model from 10 years of GOCI imagery in the East China Sea.

Long-term satellite missions could help to provide insights into spatial and temporal variations in algal blooms. However, the traditional reflectance-based method has limitations in regards to determining the available threshold for algal bloom detection among the time-varying observation conditions. In terms of extracting useful information from long-term data series precisely and efficiently, the deep learning method has shown its superiority over traditional algorithms in batch data processing. In this study, a U-net model for algal bloom extraction along the coast of the East China Sea was developed using GOCI images. The U-net model was trained with two different datasets that were constructed with six-band channels (all visible bands from GOCI imagery) and RGB-band channels (bands of 443, 555, and 680 nm from GOCI imagery). The quantitative assessment from the U-net models suggests that the U-net model trained with the six-band channel datasets outperformed the RGB-band channel datasets, with increases of 23.6%, 18.1%, and 12.5% in terms of accuracy, precision, and F-score, respectively. The validation map derived from the U-net model trained with six-band channel datasets also showed considerable matching with the ground-truth maps. By using the U-net model, the occurrence of algal blooms was automatically extracted from GOCI images. A 10-year time series of GOCI data collected between 2011 and 2020 was derived using an output-trained U-net model to explore spatial variation along the coast of the ECS. It was found that the most affected areas of the algal blooms varied by year, but were mainly located in the Zhoushan and Zhejiang coasts. Additionally, by performing principal component analysis on the daily meteorological data during April and August 2011-2020, factors related to algal bloom occurrence were discussed.

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Exploring the distribution of phosphorus (P) fractionsin soil aggregates is helpful to improve soil P availa-bility during Chinese fir planting. In this study, soil samples were collected in the 0-20 cm soil layer from Chinese fir plantations with different stand ages (9 a, 17 a, and 26 a) and one nearby abandoned land (CK) in Rongshui County, Guangxi, China. Soil aggregates were classified into >2 mm, 1-2 mm, 0.25-1 mm, and <0.25 mm size classes through dry-sieving process, and then soil P fractions in different sized aggregates were measured. These results showed that: 1) The composition of soil aggregates showed significant difference among different stand ages. As the major aggregate fractions in soil, the contents of >2 mm aggregates increased firstly and then decreased over time, and peaked in the 17 a Chinese fir plantation. The changes of soil mean weight diameter (MWD) and geometric mean diameter (GMD) during Chinese fir planting were the same as the content of >2 mm aggregates. 2) Soil total P, inorganic P, and organic P contents did not differ among different sized aggregates. However, soil available P content was mainly distributed in >2 mm aggregates with a range of 1.23-7.33 mg·kg-1. Compared with CK, soil total P, available P, and inorganic P contents were significantly higher in Chinese fir plantations, and their contents increased firstly and then decreased over time. Soil total P (322.40 mg·kg-1) and available P (7.33 mg·kg-1) contents were the highest in the 9 a plantations, and soil inorganic P content (114.05 mg·kg-1) was the highest in the 17 a plantation. Moreover, soil organic P content showed an order of 9 a > 26 a >17 a > CK, with the highest content (210.00 mg·kg-1) in the 9 a plantation. 3) The distribution of P stock in soil aggregates was related to the contents of different sized aggregates, with >2 mm aggregates having the highest P stock. Except for organic P, soil P stock increased firstly and then decreased with the increases of stand age. In conclusion, Chinese fir planting was helpful to improve soil aggregate stability and to promote the increase of soil P level before the stand age of 17 a. However, Chinese fir planting could result in the degradation of soil aggregates and in the decrease of soil P level after 17 a. The formation and stabilization of >2 mm aggregates played an important role in the maintenance of soil quality and soil P supply level after 17 a Chinese fir planting.

Phytoplankton package effect in oceanic waters: Influence of chlorophyll-a and cell size.

In this study, the interaction between the packaging effect (Qa⁎) and total chlorophyll-a concentration (Ct) or total size index (SIt) was investigated to explore the potential bio-optical mechanism in phytoplankton cells in the global oceans. In addition, the long-term spatiotemporal characteristics of these interactions were necessary for grasping their variation. Numerous in situ surface measurements (phytoplankton pigment and absorption coefficients) from the global oceans were analyzed first, and then correlation and causality analyses were performed on the satellite-deduced Qa⁎, Ct, and SIt in the global oceans during 2002-2020. The results show a negative correlation between Qa⁎ and Ct or SIt in the low latitudes (30°S-30°N) and a positive correlation in the middle latitudes (30°S-55°S and 30°N-55°N). The causality analysis reveals a mutual and asymmetric cause-effect relationship between Qa⁎ and Ct or SIt in the low latitudes. The stabilization effect of Qa⁎ contributes to a 10%-50% variation in Ct and SIt, with 40%-60% uncertainty of Qa⁎ caused by Ct and SIt in the low latitudes, which is inverse in the middle latitudes. The remaining contribution to each variable mainly originates from long-term trends and noise. Combining the analysis between Qa⁎ and the irradiance, the balancing processes in phytoplankton cells are different in the low (phytoplankton-driving mode) and middle latitudes (irradiance-driving mode), which is related to photoacclimation and photoinhibition. The analyses provide insights into the quantitative interpretation of the relationship between Qa⁎ and Ct or SIt, which contribute knowledge that has not been previously reported.

Selective synthesis of sulfoxides and sulfones via controllable oxidation of sulfides with N-fluorobenzenesulfonimide.

A practical and mild method for the switchable synthesis of sulfoxides or sulfones via selective oxidation of sulfides using cheap N-fluorobenzenesulfonimide (NFSI) as the oxidant has been developed. These highly chemoselective transformations were simply achieved by varying the NFSI loading with H2O as the green solvent and oxygen source without any additives. The good functional group tolerance makes the strategy valuable.

Understanding optical absorption associated with phytoplanktonic groups in the marginal seas.

Marine phytoplankton absorption plays an important role in oceanic biological productivity and ecological environmental dynamics. Understanding the optical absorption variability associated with phytoplanktonic groups still remains a challenge. In this study, samples (n = 206) were collected for the marginal seas of the northwest Pacific Ocean from six cruise surveys that covered different seasons. Using in situ parameters, including phytoplankton absorption coefficients and concentrations of the phytoplanktonic groups derived from phytoplankton pigments collected with high-performance liquid chromatography (HPLC), we developed a Gaussian model to characterize the specific absorption spectra of eight phytoplanktonic groups, including diatoms, chlorophytes, cryptophytes, cyanobacteria, prymnesiophytes, prasinophytes, dinoflagellates, and chrysophytes, without the package effect. The model was established by accurately identifying for the numbers and locations of the Gaussian peaks and their corresponding half-wave widths. The proposed model produced promising results, and a leave-one-out cross validation generated R2 values exceeding 0.7 for the whole visible light range and above 0.85 (correspondingly MAPE <40%) for the simulated wave bands, excluding the range of 550-650 nm. Meanwhile, a comparison with several spectra observed in the lab showed a high degree of similarity, indicative of the superior performance of our model. Applying the documented specific absorption spectra to the investigated water bodies (whether water surface or profiles) enabled us to quantify the absorption coefficients from different phytoplanktonic groups and characterize their relative contributions to the total. The findings of this study support our understanding of the dynamics of phytoplankton community structure with optical data.

Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea.

Euphotic zone depth (Zeu) plays an important role in studies of marine biogeochemical processes and ecosystems. Remote sensing techniques are ideal tools to investigate Zeu distributions because of their advanced observation ability with broad spatial coverage and frequent observation intervals. This study aims to develop a new approach that derives Zeu directly from remote sensing reflectance (Rrs(λ)) values rather than by using other intermediate variables and then reveals the dynamic characteristics of Zeu in the Bohai Sea (BS) and Yellow Sea (YS). To do this, in situ data collected from various seasons were first used to assess the ability of several spectral indicators of Rrs(λ) for deriving Zeu and the optimal spectral indicator was determined to build a Zeu retrieval model. This model was further applied to Geostationary Ocean Color Imager (GOCI) data to study the spatial and temporal variations in Zeu. The results showed that the new Zeu retrieval model performed well with R2, RMSE and MAPE values of 0.843, 4.42 m and 17.9%, respectively. High Zeu levels were generally observed during summer for both coastal and offshore waters while the lowest Zeu values were observed during winter. Changing concentrations of total suspended matter, which are often modulated by sediment resuspension and transportation, are probably the main factor responsible for the spatial and temporal variability of Zeu. These findings provide crucial information for modeling primary production, carbon flux, and heat transfer, etc., in the BS and YS, as well as contribute a useful alternative approach that will be easily implemented to study Zeu from satellite data for other water environments.