This study implemented a discharge energy and success-rate monitoring system to replace the traditional oscillograph observation method and conducted a microbial control test for a nanosilver colloid prepared by an Electrical Discharge Machine (EDM). The advantage of this system is that the discharge conditions can be instantly and continuously observed, and the optimized discharge parameter settings can be recorded. The monitoring system can use the arcing rate to control the energy consumption of the electrodes to standardize the nanosilver colloid. The results show that the arcing rate, electrode weight loss, and absorption peak wavelength are very accurate. The nanosilver colloid prepared by EDM is free of any chemical additive, and in comparison to other preparation methods, it is more applicable to biotechnology, even to the human body. The microbial control test for the nanosilver colloid included a Bathroom sample, Penicillium, Aspergillus niger, and Aspergillus flavus. In test solution NO.1 (prepared by micro-EDM), the effects of all four samples were inhibited at 14mm in a metal ring experiment, and in the cotton pad experiment, Penicillium was inhibited at 17 mm. In the metal ring experiment, test solution NO. 2 (prepared by EDM) had an effect at 20 mm on the bathroom samples, but at only 15 mm on flavus. In the cotton pad experiment, the inhibited effect was more effective in Penicillium and Aspergillus Niger; both inhibited effects occurred at 25 mm. Test solutions NO.3 (prepared by micro-EDM) and NO.4 (32 ppm Ag+) had a 14–15 mm effect on all samples in the metal ring experiment. In the cotton pad experiment, NO.3 had an effect on Penicillium at 19 mm while the effect on the others occurred at 14 mm, and NO.4 had an effect at 25 mm in Penicillium and Aspergillus Niger, and only at 14 mm in the bathroom and Aspergillus flavus samples. Nanotechnology, biotechnology, and information technology are three basic technologies in the 21st century . Nanotec2, SiO2, and nanosilver, and the annual input of labor, financial resources, material resources, and turnover has increased in recent years. Nanotechnology development has been an important technical means for adding industrial value [In addition, as the nanosilver technique gradually becomes mature, the application of nanosilver to the market of paints, pigments, and coating is estimated to increase in the future ,8. In teal value . The maiThere are two ways to fabricate nanoparticles: one is physical, and the other is a chemical method. The chemical way uses the “bottom-up” method, which is similar to the “self-assembly” technology of substances and functional substances produced by nature. These methods are all constructed from the level of the molecule to the nanoscale. The physical preparation method is generally a “top-down” etching technique. Mechanical pulverization and grinding use higher-hardness materials as a medium to grind particles by shear force, friction force, and impact force to break down the particles to a small size.The electrical discharge machine (EDM) is traditionally used for processing metal materials with high toughness and hardness ,11. Its Power system: 100 DC volts and above;z-axis motor to maintain the two electrodes at a distance of micrometers;Servo control system: controls the z-axis speed, etc.Parameter control panel: adjusts the discharge cycle or The proposed EDM system mainly consists of the following sub-systems:on is the discharging time, when the electrodes will successfully carry out spark discharge; Toff is the stopping time. The period (Ton + Toff) will continuously repeat during the processing time, for example, 20 min and 40 min in this study. When the discharge is successful, the period Ton when the pulse voltage appears is composed of a period of spark discharge ignition delay time and a period of spark discharge time. When the discharge is successful, the initial stage of the pulse voltage is the ignition delay time, and the electric field strength provided by the pulse voltage during this period is not enough to break down the dielectric of the electrode gap. Therefore, the voltage between the gap (VIEG) will be maintained at the open circuit voltage, and the current between the gap (IIEG) will be 0A, as shown in IEG rapidly rises to a maximum value, and VIEG drops to a very low voltage value, during which spark discharge occurs between the tool and the workpiece, as shown in off, the electrode gap will immediately end the spark discharge state because no pulse voltage provides the energy required for discharge. During the Toff period, IIEG and VIEG both drop to zero, as shown in off, the electrode gap will gradually recover the insulation, and the insulation degree of the electrode gap at the end of Toff will affect the ignition delay time of the next cycle of discharge. In addition, after a successful electrode discharge, the deionized water (DW) will be restored to a state of insulation in order to facilitate the next cycle of discharge and eliminate the metallic particles between the electrodes. Therefore, the Ton-Toff settings affect processing efficiency and quality [Discharge failure (situation 1): There is voltage without a current. This is the same as with an open circuit.Discharge failure (situation 2): As the two electrodes are very close, it is likely to cause a short circuit, similar to a current without voltage.Discharge success: The spark damages the DW insulation and successfully generates a spark discharge. In addition, there are voltage and a current at the same time.The EDM monitoring system has traditionally used an oscillator to observe the voltage and current wavelengths between electrodes, as shown in  quality . There a quality ,24,25 asNanometal colloids, such as nanogold, nanosilver, nano-copper, nano-aluminum, and nano-titanium, can be made with any method able to conduct electricity using an EDM ,28,29,30Absorption peak: The instrument will emit UV and visible light to radiate the object under analysis. Through the sensor receiving the light, it can measure the absorption peak of each wavelength of the colloid. Higher absorption peaks suggest higher concentrations of colloid at the wavelength. On the contrary, a lower absorption rate suggests a lower concentration of colloid ,34,35.Wavelength of the highest absorption peak: Nanoparticles will radiate under the stimulation of certain wavelengths. For example, nanosilver has the highest absorption value around 400 nm , while nThe nanometal colloids can be analyzed using a spectrophotometer, which can measure two indicative parameters:As an EDM during discharge has no cyclic changes, and the frequency is very high, the discharge feature cannot be observed using an oscillator ; howeveroff will affect the ignition delay time of the next cycle of discharge, so the stirring moves the nanoparticles away from the gap between the electrodes to make the gap recover the insulation more quickly. The oscilloscope is used to observe the voltage and current of the gap between the electrodes. In Z-axis. CAPACITOR is used to set the capacitance value and is proportional to the transient current of discharge pulse at Ton. Ton and Toff control the discharge and off time of the electrodes. Polarity adjusts the polarity of the upper and lower electrodes. SERVO controls the servo motor speed and is proportional to the motor speed. Stabilizing controls the sensitivity of the feedback circuit and is also proportional to the motor speed. HV switches the DC power supply from 140 V to 240 V. In addition, Ip is proportional to the discharge current and processing rate, and inversely proportional to precision.The EDM vaporizes the silver wire into nano-sized silver particles. The working electrodes and workpiece in this study are distinguished as electrodes. The electrode connected to positive electricity is the anode, while that connected to negative electricity is the cathode. The nanosilver colloid is prepared by ESDM in this study. The silver wire (with a diameter of 1 mm) is ground into nano-sized (1~100 nm) silver nanoparticles by the high temperature of the ESDM . The disThis study integrated multi-field technology research and successfully developed a micro-EDM set as shown in Test solution preparation: NO.1 was the nanosilver colloid made using the micro-EDM, with a silver ion concentration of 5 ppm. NO.2 was the nanosilver colloid produced by the traditional EDM; the silver ion concentration was 32 ppm, and the silver particle concentration was about 300 ppm. NO.3 was the nanosilver colloid produced by the micro-EDM; while the silver ion concentration was 5 ppm, the nanoparticle was the smallest. NO.4 was a 32 ppm silver ion titer.Fungus sample preparation: There are four kinds of fungus samples: (a) the strain was randomly collected from the dim and damp parts of a bathroom; the strain was smeared on the Potato Dextrose Agar (PDA) and cultured; (b) penicillium: the strain was collected from moldy oranges; the strain was smeared on PDA and cultured; (c) Aspergillus Niger: pure strain was bought from BCRC ; the strain was smeared on Malt Extract Agar (MEA) and cultured; (d) Aspergillus Flavus: pure strain was bought from BCRC; the strain was smeared on PDA and cultured. The bathroom sample, Penicillium, Aspergillus niger, and Aspergillus flavus are the four targets in this study. These are widespread both indoors and outdoors, and those exposed to them will sometimes have allergies, get sick, or suffer an infection or other conditions that may harm the body. These four targets are easily obtained, simple to cultivate, and most importantly, they are often sources of trouble in normal life in Taiwan (due to the wet weather). Therefore, this study used the micro-EDM to fabricate a nanosilver colloid that can inhibit the four targets ,44.Experimental method design: Inhibition zone test: the size of the inhibition zones formed by the NO.1~NO.4 test solutions in four fungus culture media were observed in order to judge the microbial control effect of each test solution. The test process is shown in The other main purpose of the study was to use the traditional EDM and the micro-EDM that produced the nanosilver colloid to evaluate its effectiveness in the microbial control of fungi; as the particle size, zeta potential, and concentration were different, so its physical properties and chemical properties were also different. The study procedures were divided into following:Cotton pads with a diameter of 140 mm were labeled 1, 2, 3, and 4, soaked in the NO.1~NO.4 test solutions, respectively, and placed in the culture media cultivating different strains; the inhibition zone sizes of the cotton pads were observed to judge the microbial control effects . The tesgap. The Vgap was 0.0526 times that of the interelectrode gap voltage. The Igap signals of the circuit were equal to the current that flows through the electrode gap. The conditions for the circuit to judge the successful discharge were 0.5 V ≦ Vgap ≦ 2.4 V and Igap ≥ 2.4 A. If the discharge was successful (met the criteria above), the signal output from the circuit to the counting pin of the RT-DAC4/PCI card of the VisSim was 1 (counting pin = 1); on the contrary, if the discharge was not successful, the counting pin = 0. The discharge success rate was monitored through the signal transmission output by the discharge success rate circuit to the CNT0 counter of the RT-DAC4/PCI card, and the signal was processed by VisSim to obtain the discharge success rate and the cumulative number of successful discharges . The flow chart of the discharge success rate counting is shown in D is the cumulative number of successful sampling and discharging events in time Ton; Ntotal is the total number of discharge samplings in time Ton; Dcycle is the duty cycle (Ton + Toff); tproc is the production process time; and fsample is the sampling frequency. This study was able to obtain the total discharge success times and determine the signals through this digital input/output interface card. It can replace the complex electrical circuit, which can count more than 1 million times per minute. The VisSim software used in this study is PC-based. By using the PC-based VisSim, this study was able to observe the real-time discharge times. In addition, it immediately computed the successful discharge times, electrode energy consumption, and discharge success rate, as shown in The micro-EDM was used to prepare the nanosilver colloid for test solution NO.1, and the related parameter settings are described in The traditional EDM was used to prepare the nanosilver colloid for test solution NO.2, and the related parameter settings are described in + standard solution.The micro-EDM was used to prepare the nanosilver colloid for testing solution NO.3. In addition, the zeta potential was −40 mV, as shown in The experimental results of the inhibition zone test  are shown in The results of the inhibition zone tests are described as follows. In addition, the results are shown in In the inhibition zone test, the metal ring was placed on the culture medium, and the test solution was then injected into the metal ring . The tesThe microbial control cotton pad test was an improvement proposed for inhibition zone testing ,50. CompThe microbial control cotton pad test results were relatively objective and observable. It was observed that the NO.2 and NO.4 test solutions had the best microbial control effects.+ standard solution. It was observed that the NO.2 32 ppm nanosilver colloid had the best microbial control effect, then the NO.4 Ag+ standard solution at the same concentration. It may be that, because the silver nanoparticles release Ag+ continuously at the same Ag+ concentration, the microbial control effect is better than the standard Ag+ solution. While the concentration of the NO.1 and NO.3 nanosilver colloids was about 5ppm, NO.3 had the smallest silver nanoparticle, meaning a larger contact surface area and the highest zeta potential; thus, its microbial control effectiveness was better than NO.4.The inhibition zone test was implemented for four kinds of fungi in the NO.1~NO.3 nanosilver colloids with different concentrations and characteristics and the NO.4 AgComparing the two inhibition zone tests, the metal ring limited the expansion of the inhibition zone when the fungus grew, so it is difficult to observe the actual microbial control effect. The user may adjust the successful discharge times, electrode energy consumption, and discharge success rate at any time to obtain the optimal parameters to fabricate the nanosilver colloid using the Electrical Spark Discharge Method.In the inhibition zone experiment, this study proposes use of the microbial control cotton pad. The microbial control cotton pad is characterized by its low cost, quick experimentation, and easy observation. It is unlikely to fail, and there is no metal ring; thus, the presentation of the inhibition zone will match the actual result better.In the NO.1 liquid, the effects were inhibited at 14 mm in all four samples in the metal ring experiment and at 17 mm in Penicillium in the cotton pad experiment. In the metal ring experiment, the NO.2 liquid had an effect at 20 mm in the bathroom samples and a 15 mm inhibited effect on flavus. In the cotton pad experiment, the inhibited effect was more effective in Penicillium and Aspergillus Niger, both with an inhibited effect at 25 mm. The NO.3 and NO.4 liquids had a14–15 mm effect on all samples in the metal ring experiment. In the cotton pad experiment, NO.3 had an effect on Penicillium at 19 mm, while its effect on the others was only 14 mm. NO.4 had an effect of 25 mm on Penicillium and Aspergillus Niger and only 14mm on the bathroom and Aspergillus flavus samples.+ and nanosilver colloids have a better microbial control effect on penicillium and Aspergillus niger and a worse effect on Aspergillus flavus.The inhibition zone experiment found that the AgAlthough this study has verified that a nanosilver colloid made using an EDM has microbial control effects, it is only a small step. The issue of nanomaterials is a big subject in terms of antibacterial, biomedical, and environmental aspects. All of the research topics are only just beginning. It is worth investing in more research to benefit more people in the near future.There are two ways to fabricate nanoparticles: one is physical (the “bottom-up”), and the other is a chemical (the “top-down”) technique. The chemical method uses chemical agents, which is not environmentally friendly. In addition, other physical methods consume energy/time and cannot instantly monitor the process. This study developed a real-time monitoring system for the Electrical Spark Discharge Method (ESDM) using a micro-Electrical Discharge Machine. This study has two limitations. One is that the ESDM is a physical method and, unlike the chemical way, cannot obtain the precise size and concentration of the nanoparticle. The other is that the inhibition of Niger cannot obtain a precise concentration but a relative one. However, all the experiments in this study were conducted with a standardized process in order to reduce the errors made by the human hand. With this system, the micro-EDM can obtain the successful discharge times, electrode energy consumption, and discharge success rate. The conclusions of this study are as follows:


Trace metal pollution in coastal seas has been of great concern because of its persistence, toxicity, and biological accumulation through the food chain. The role of sea ice in trace metal transport and distribution in Liaodong Bay is still unknown. Sea ice and water samples were collected in Liaodong Bay in February 2021 to assess the distributions of Cu, Pb, Cd, Zn, Cr and Hg during the frozen season. Total dissolved (<0.45 μm) and particulate (>0.45 μm) heavy metal concentrations were measured by atomic absorption spectrophotometry  and atomic fluorescence spectrophotometer (Hg). The ice held significantly higher levels of total Cr when compared to water. There were no significant differences in total concentrations of Cu, Pb, Cd, Zn and Hg between water and ice samples. An analysis of dissolved-to-total metal ratios shows that all studied metals in the dissolved phase, except Hg, are found exclusively in Liaodong Bay nearshore ice as a result of desalination. Concentrations of particulate metals are higher in sea ice than in seawater due to suspended/bed sediment entrainment and atmospheric deposition. The partitioning coefficients of six trace metals are not increased with the increase in the concentration of particulate matter in sea ice due to sediment accumulation. The redistribution of trace metals between seawater and ice was a result of comprehensive effects of physico-chemical processes and environmental factors, such as chemical oxygen demand, salinity, and suspended particulate material. With thmisphere ,5.Sea ice has a significant impact on the biogeochemical processes in cold regions. Besides heat and salinity, the formation, drift and melting of ice contribute to the redistribution of the pollutants in marine systems. When the sea water freezes into ice, the salt will remain in the water due to the repulsive effect. Therefore, the formation of sea ice will increase the salinity of a region, while the melting of ice often has the opposite effect.Unlike the desalination process of the rejection of salt, sea ice seems to accumulate trace metals . DissolvDirect releases from the ice of particulate heavy metals, such as Fe and Cu, cause the surface concentration of seawater to capture a peak quickly after the pack ice melts . LaboratAlthough research on both the Arctic and Antarctic regions demonstrates that sea ice accumulates trace metals, the enrichment effect of heavy metals in other regions does not always work . LaboratThe present attention has primarily been focused on the polar seas, which are covered by sea ice for most of the year. In some mid-latitude sea areas, sea ice also appears every winter. The most southerly site in the northern hemisphere where an extensive sea ice cover forms is the Bohai Sea, located off the east coast of China between the latitudes of 37° and 41° N. As one of three bays of the Bohai Sea, Liaodong Bay has the longest frozen period, which normally lasts 3–4 months from November to February. During a mild winter, ice forms only in the northern part or nearshore of Liaodong Bay, but during a cold winter the whole Liaodong Bay is covered in ice. Liaodong Bay is a severely impacted urban estuary, as inputs of contaminants to the estuary from riverine sources, urban sewage discharge, agricultural runoff, maritime vessels, atmospheric deposition and accidental spills have become increasingly significant over the past five decades.At present, there is a great deal of research on the spatial distribution, temporal evolution and water–sediment exchanging process of heavy metals in the Liaodong Bay ,18,19. HThe present work provides new data on the spatial distribution and partitioning between water and ice of six heavy metals (copper (Cu), lead (Pb), cadmium (Cd), zinc (Zn) chromium (Cr), and mercury (Hg)) in Liaodong Bay. Its specific aims are to (i) assess how ice influences behavior of different trace metals and their fractions; (ii) examine if the coastal ice is able to contribute to accumulating high levels of trace metals; (iii) analyze factors affecting trace metal distribution.According to the national marine functional zoning and the marine functional zoning of Liaoning Province, the coastal waters of Liaodong Bay are selected as the survey area , and theThe recovered ice samples were melted in light-proof conditions at room temperature. All sampling, on-site treatment and analysis methods were performed with reference to the Marine Monitoring Specification Part 4: Seawater Analysis and were strictly conducted through quality assurance (QA) and quality control (QC) ,21. BothKd) of a particular trace metal between the particulate and dissolved fractions is defined as the ratio of the trace metal fraction in the particles  to that in the dissolved concentration , as given in Equation (1). For the convenience of comparison, the logarithmic value is usually used.The partition coefficient , lead (TPb), cadmium (TCd), zinc (TZn), chromium (TCr) and mercury (THg) in the water range between 8.78–76.70 (avg. 40.65 ± 18.63), 2.92–33.21 (avg. 21.85 ± 8.26), 3.34–13.06 (avg. 7.78 ± 2.07), 11.57–58.76 (avg. 25.99 ± 10.63), 9.30–48.64 (avg. 34.19 ± 7.68), and 0.002–0.064 (avg. 0.025 ± 0.019) μg/L, respectively . The aveConcentrations of TCu, TPb, TCd, TZn, TCr and THg in the ice range between 23.51–98.49 (avg. 41.81 ± 14.72), 14.97–62.17 (avg. 26.92 ± 9.22), 0.66–25.33 (avg. 9.21 ± 5.28), 14.83–64.68 (avg. 23.80 ± 9.77), 10.66–72.76 (avg. 40.28 ± 15.28), and 0.002–0.130 (0.038 ± 0.031) μg/L, respectively. The average total metal concentration is in the order Cu > Cr > Pb > Zn > Cd > Hg. The coefficients of variation (CV) of TCu, TPb, TCd, TZn, TCr and THg in sea ice are 35.2%, 34.3%, 57.4%, 41.1%, 37.9% and 82.7%, respectively. Higher inter-sample variability of Cd, Cr, and Hg are found in ice phases, and variability of Cu in ice samples is significantly lower than that in seawater.There are many cities along Liaodong Bay, and the Daliao River, Liaohe River, Daling River, etc., that flow into this area, gathering a large number of terrigenous materials from the drainage basin. In spring, summer and autumn, the concentration of trace metals in the northern, top area of Liaodong Bay is generally higher than that in the eastern and western coastal seas of Liaodong Bay. Nevertheless, this spatial feature is not obvious in winter. The type of sea function is a more important factor in determining the levels of trace metals. The concentrations of heavy metals in the industrial sea area are significantly higher than that in other functional areas .t test is used to further statistically analyze the metal levels in two phases. It is found that ice holds significantly higher levels  of TCr compared to water. There are no significant differences in concentrations of TCu, TPb, TCd, TZn and THg between the water and ice samples .The mean ratios of total trace metals between sea ice and seawater are 1.41 (Cu), 1.51 (Pb), 1.21 (Cd), 0.97 (Zn), 1.20 (Cr) and 2.48 (Hg), respectively. It seems that most trace metals are enriched in sea ice. The The redistribution effect of sea ice on total concentrations of trace metals does not seem to be significant. There is neither significant enrichment of heavy metals such as polar sea ice nor obvious extrusion effect like that of freshwater lakes ,23. The Another overlooked factor is that the concentration of trace metal in Liaodong Bay is much higher than that in polar seas. Considering the concentration effect, the issue of whether the migration law of trace metals between ice and seawater is applicable to Liaodong Bay needs further study.4), salinity , and suspended particulate material (SPM). COD of seawater ranges from 0.09 to 1.98 mg/L, with an average of 0.58 mg/L, while it varies from 0.14 to 2.83 mg/L in the ice, on an average of 0.83 mg/L. The salinity  of coastal waters in the survey averaged 31.3 and below 30 during the ice-free period. Suspended particulate material (SPM) concentrations in Liaodong Bay are high and range between 20.1–146.2 mg/L. Concentrations of SPM in seawater ranges from 0.01 to 0.16 mg/L, on an average of 0.06 mg/L (n = 30), values which are in good agreement with those previously found in the nearshore waters of Liaodong Bay. Concentrations of SPM in the sea ice are about 4 times higher than those in seawater, ranging from 1.0 to 1544 mg/L, with an average of 156.8 mg/L (n = 30).Other than trace metal, some other seawater properties are measured, such as COD , 13.74–59.75 (avg. 25.55 ± 9.31), 0.36–21.59 (avg. 6.84 ± 4.96), 8.98–51.71 (avg. 17.44 ± 8.57), 7.35–65.67 (avg. 37.02 ± 14.51), and 0.001–0.079 (avg. 0.029 ± 0.024) μg/L, respectively. Concentrations of DCu, DPb, DCd, DZn, DCr and DHg in the sea ice range from 0.52–4.99 (avg. 2.11 ± 1.24), 0.42–4.81 (avg. 1.37 ± 1.15), 0.28–4.36 (avg. 2.37 ± 1.10), 2.52–12.97 (avg. 6.36 ± 2.39), 1.79–11.76 (avg. 3.26 ± 2.34), and 0.001–0.051 (avg. 0.009 ± 0.012) μg/L, respectively. The dissolved-to-total metal ratios of Cu, Pb, Cd, Zn, Cr and Hg in sea ice are 5.5%, 5.7%, 32.1%, 27.7%, 9.0% and 24.4%, respectively. It is found that all studied trace metals of dissolved phase are found almost exclusively from coastal ice in Liaodong Bay. The ratios of particulate heavy metals between sea ice and seawater are 1.73 (Cu), 1.80 (Pb), 1.97 (Cd), 1.25 (Zn), 1.27 (Cr) and 2.65 (Hg), respectively. It can be seen that all heavy metal particulate states are concentrated in ice.The ratios of dissolved trace metals between sea ice and seawater were 0.52 (Cu), 0.54 (Pb), 0.65 (Cd), 0.67 (Zn), 0.95 (Cr) and 3.12 (Hg), respectively. It can be seen that all metals of dissolved states, except Hg, are expelled during the process of freezing. Concentrations of DCu, DPb, DCd and DZn are significantly lower in sea ice compared to the ambient water. It has been previously reported that the concentration of DCd in ice is lower than that in seawater . In contThe source and distribution of heavy metals in the coastal area are mainly attributed to human activities  and natural factors . By means of a correlation analysis, we can speculate whether the sources of heavy metals are consistent or whether the geochemical properties of elements are similar.p < 0.05 level. Aside from Hg, all elements have positive significant correlation with each other, which indicates that their sources and environmental behaviors are the same or similar, and they are affected by human activities to a similar extent.The relationship between the six metals and the physicochemical properties of seawater is investigated using simple linear regression . A coeffEnhanced correlation between trace metals in sea ice exhibits their similar migration and redistribution during ice formation , and allSediment particles are instrumental in controlling the transport processes between the water column and bed sediments. On one hand, the concentration of particulate trace metals increases with the increase in the concentration of suspended sediments in water. On the other hand, the increase in the concentration of suspended sediments will produce a “particle concentration effect”, reducing the adsorption capacity of particles to heavy metals . The twoSPM concentrations in ice range between 1.1–1544 mg/L, approximate 4.3 times the variation in water. Sediment-laden sea ice is a ubiquitous phenomenon in the frozen seas, and it covers more than a half faction of the total ice coverage, with a maximum of 80–90% in Liaodong Bay. The sea ice in Liaodong Bay is first formed near the northern coastline. Under the action of tide, current and wind, sea ice frequently scrapes the seabed, and a large amount of sediment enters the ice body. However, there is no corresponding increase in the levels of trace metals in sea ice, because the nearshore sediment size is relatively large with low adsorption of heavy metals .The salinity  of coastal waters in the survey averaged 31.3 and was below 30 during the ice-free period. With increasing salinity in water, most trace metals (except for Hg) exhibited an evident rise, especially for Pb, Cd, and Cr. A considerable number of dissolved trace metals, like salts, are redistributed from ice to the surrounding water during the freezing process. Moreover, the increase in salinity will produce a “salinity effect” and promote the desorption of trace metal ions from suspended particles .Kd in both water and ice phases are plotted against SPM concentrations on a logarithmic scale in Kd in the water phase increase in the order of Cd < Zn < Hg < Cu < Pb < Cr, consistent with previous results from Galveston Bay [Kd in the ice phase are in the order of Cd < Zn < Hg < Cr <Cu < Pb.Values of ston Bay , while tKd of Cu and Cd, there is no evident difference between water and ice. The flux of atmospheric deposition Pb is greater than the river discharge in Liaodong Bay [Kd of Pb rises in ice. The Kd values of Zn, Cr, and Hg decline in the ice phase, but for different reasons. Dissolved Hg in ice is relatively more difficult to volatilize into the atmosphere than that in water, resulting in its higher dissolved content in ice. Due to the rubbing between sea ice and the seabed, a large amount of sediment with large size on the seabed is mixed, which increases the concentration of SPM without increasing the corresponding particulate Cr. The enrichment of organic matter in ice increases the chance of Zn bonding with organic matter to become dissolved state.For dong Bay . In wintKd on SPM concentrations for Pb, Cd, Zn, and Hg, but there are large changes for Cu and Cr. It appears that PCE for each metal is changeable in other estuaries and coastal regions. Wen et al. (1999) found that it is noticeable only for Cu, and that the Kd values of Pb, Cd, and Zn were nearly independent of SPM concentrations [An evident negative relationship between the particulate/solution partition coefficient of all trace metals and suspended particulate matter can be seen in trations . PCE varWe reported the concentrations of trace metals  in both water and ice to understand the sea ice environment of Liaodong Bay. Compared with other seasons, the pollution level of trace metals in Liaodong Bay is lower in winter. Decreasing terrestrial input and strong mixed effect of water contribute to a decline in spatial variability.This study shows that there is a varied enrichment for different trace metals during the freezing of seawater, which is probably caused by their physico-chemical properties and environmental factors. Except for Cr, the rest of the five metals do not appear to be significantly enriched in sea ice as compared to seawater. In general, the dissolved levels of all metals are elevated as a result of desalination, with the exception of Hg, and the particulate levels are elevated due to sediment entrainment. However, the partitioning of these trace metals does not show strong bias towards the particulate phase in ice, because incorporated incorporation bed sediments with large size absorb relatively few trace metals.It should be pointed out that the sampling sites in this survey are all located nearshore. To understand the impact of sea ice on the environmental behavior of trace metals, the investigation scope should be extended to offshore areas. Further attention should also be paid to the relationship between the trace metals and other substances, such as nutritional components and persistent organic pollutants.


Ice discharge from 2000 to 2020 was equivalent to 2.10 ± 0.22 mm of sea-level rise and comprised approximately 79% of frontal ablation, with the remainder from terminus retreat. Near-coastal areas most impacted include Austfonna, Svalbard, and central Severnaya Zemlya, the Russian Arctic, and a few Alaskan fjords.In the Northern Hemisphere, ~1500 glaciers, accounting for 28% of glacierized area outside the Greenland Ice Sheet, terminate in the ocean. Glacier mass loss at their ice-ocean interface, known as frontal ablation, has not yet been comprehensively quantified. Here, we estimate decadal frontal ablation from measurements of ice discharge and terminus position change from 2000 to 2020. We bias-correct and cross-validate estimates and uncertainties using independent sources. Frontal ablation of marine-terminating glaciers contributed an average of 44.47 ± 6.23 Gt a As glaciers terminate into the ocean, mass is lost through frontal ablation where the ice meets the ocean. Here the authors estimate decadal frontal ablation from 2000 to 2020 of 1496 glaciers in the Northern Hemisphere, and find that frontal ablation makes up 79% of ice discharge to the ocean. Quantifying frontal ablation is essential to partitioning glacier mass loss components, which informs sea-level budgets, estimates of glacier freshwater contributions to the ocean, impacts on marine ecosystems and iceberg hazards. Recent model results suggest that Northern Hemisphere frontal ablation was around 39 Gt a−1 from 1980 to 19992. Frontal ablation accounted for 10% of the 882 Gt a−1 global glacier ablation rate (which includes surface melt), although about half of this occurred in the Southern Hemisphere2. The same modeling study projected a Northern Hemisphere frontal ablation rate of 50.6 ± 23.8 Gt a−1 for 2020–20402. However, observation-based estimates of frontal ablation have been limited, partially because many studies only quantify ice discharge4 as they do not include mass changes due to terminus retreat or advance, or these are only computed for individual glaciers5. Alaska6 and Svalbard7 are the only regions in the Northern Hemisphere with complete observation-based frontal ablation estimates, but these have not been updated since 2013.When glaciers terminate in the ocean, mass is lost by frontal ablation at the ice-ocean interface, including mass loss due to iceberg calving , submarine frontal melting, and subaerial frontal melting and sublimation11, satellite gravimetry13, and numerical modeling16, no study has determined the frontal ablation rate for the entire Northern Hemisphere. This has mainly been due to a previous lack of spatially and temporally consistent glacier ice thickness, surface velocity, and terminus position observations, from either field or remote sensing surveys, which is exacerbated at high latitudes.Whereas many regional-scale studies have derived regional total glacier mass changes from glaciological and geodetic methods18. The residual examples are primarily within Franz Josef Land, Russia17.Here we identify every marine-terminating glacier in the Northern Hemisphere, distinct from the Greenland Ice Sheet, and use measurements or estimates of ice thickness, surface velocity, and terminus position changes, together with a climatic mass balance model, to estimate mean frontal ablation 20. The Greenland Periphery has the most marine-terminating glaciers (537), followed by the Russian Arctic (412), Arctic Canada North (252), Svalbard and Jan Mayen , Arctic Canada South (86), Alaska (42), and Iceland (1). However, the length of terminus flux gates in Russia is more than two times that of Greenland Periphery glaciers (Table Guided by the Randolph Glacier Inventory version 6.0 (RGI6)−1  between 2000 and 2010, and 51.98 ± 4.62 Gt a−1 between 2010 and 2020  for a single glacier, but was surpassed by Basin-3 of Austfonna in Svalbard (6.10 ± 0.24 Gt a−1) during the next decade  will modify this list.Most marine-terminating glaciers (87% of the 1496 glaciers) contribute <0.04 Gt aTo investigate which parts of the ocean are most affected by frontal ablation, and thus susceptible to related iceberg hazards and marine ecosystem impacts, we introduce an ‘intensity index’ that spatially aggregates frontal ablation from all glaciers occurring within 50 km of any point in the ocean on a 10 km grid Fig. . The ind23, in addition to substantial contributions from the rest of the ~1200 km2 ice cap. High indices are also described in the strait between October Revolution and Komsomolets islands in Severnaya Zemlya  of glaciers in Franz Josef Land, the large number of glaciers yields a high index.The highest intensity index occurs around northeastern Svalbard, due to the vigorous surge of Basin-3 of Austfonna which started in 2012Quantifying the relative importance of ice discharge versus terminus retreat is key to understanding mass loss mechanisms and highlights where future efforts should be focused to reduce observational uncertainties. Terminus retreat was most important in Arctic Canada South, Arctic Canada North, and Greenland Periphery, where it made up 67%, 48%, and 41%, respectively, of total frontal ablation, while only amounting to 8% in Alaska. Thus, ice discharge is dominant in controlling frontal ablation rates in Alaska.24 had a frontal ablation rate of 0.20 ± 0.17 Gt a−1 from 2000 to 2010, compared to 1.88 ± 0.23 Gt a−1 in 2010–2020 due to the 18.91 ± 0.28 km2 a−1 terminus retreat during that decade, the largest of any Northern Hemisphere glacier. On the other hand, the surging outlet of Vavilov Ice Cap25 discharged 1.24 ± 0.01 Gt a−1, but frontal ablation was only 0.29 ± 0.10 Gt a−1, due to terminus advance. Both these events are unique because the Matusevich Ice Shelf is now gone, and Vavilov Ice Cap is unlikely to surge again in the coming decades as no previous surge events have been identified since at least the 1980s, indicating a very long quiescent phase26. For the entire Northern Hemisphere, the total terminus mass loss of 11.57 ± 3.81 Gt a−1 during 2010–2020 consisted of 2.98 ± 0.70 Gt a−1 of terminus advance and 14.54 ± 5.97 Gt a−1 of terminus retreat.For a retreating glacier, frontal ablation is larger than ice discharge across the flux gate; conversely, for an advancing glacier, frontal ablation is lower than ice discharge. Two examples in Severnaya Zemlya illustrate the connection between terminus change and frontal ablation. We found that the eight glaciers that fed the now collapsed Matusevich Ice Shelf27 consistent with dynamic instabilities such as surging or pulsing (hereafter surge-type glaciers). During the surge phase, these glaciers have elevated velocities, typically by an order of magnitude or more above normal, for months to years, which can lead to increased frontal ablation over a similar period30. Of the 45 glaciers that advanced during the 2000–2010 period, we found 13 confirmed, two probable, and five possible surge-type glaciers, whereas 25 showed no signs of instability, in total accounting for 6.74 ± 0.40 Gt a−1 of frontal ablation. From 2010–2020, 39 glaciers advanced, of which 14 were confirmed, five probable, and four possible surge-type glaciers, while 16 showed no signs of instability, in total accounting for 11.19 ± 0.71 Gt a−1. Only 13 glaciers, six of which are surge-type, advanced over both 2000–2010 and 2010–2020, compared to 745 glaciers that retreated during both time periods.We examined glaciers with advancing termini for morphological indicators1. We subtract our frontal ablation estimates from total mass balance estimates9 derived from elevation change observations of all glaciers in a region to estimate the regional climatic-basal balance. Since these estimates9 do not include any mass changes below sea level due to retreat or advance, we correct these geodetic balances assuming two end-member scenarios (see “Methods”) of 5.16 to 9.29 Gt a−1 of ice lost below sea level from 2000 to 2020. This suggests that the Northern Hemisphere glacier net mass loss of 223.7 ± 14.6 Gt a−1 from 2000–2020 by Hugonnet et al.9 is currently underestimated by 2–4%, although this portion will not contribute to sea-level rise. We find a total mass loss due to ice discharge equivalent to 2.10 ± 0.22 mm of sea level rise between 2000 and 2020 , with an additional 0.11 ± 0.11 mm coming from terminus mass loss above sea level.Total glacier mass balance is equal to the climatic-basal balance  and frontal ablation−1) than the total net mass loss rate  in Svalbard, which has overlapping uncertainties with published estimates32. All other regions have negative climatic-basal balances. Estimates of climatic-basal balance exist for one other region, Greenland Periphery16, with which we find agreement.In the Russian Arctic, frontal ablation is greater , which advanced to become marine-terminating between 2000 and 201036 as having either a weak (CL1) or no (CL0) hydrological connection to the ice sheet. Our total number of glaciers and terminus outlines differs from classification of the RGI due to missing glaciers10, poorly mapped ones, and misclassified terminus types. Poorly mapped glaciers in RGI6 include those with multiple distinct termini and glaciers that share one terminus .For Greenland Periphery, beyond the ice-sheet margin, we included glaciers that were defined by Rastner et al.10. Unconstrained ice caps that terminate in the ocean, such as those found in the Russian Arctic, have one flux gate that encircles the ice cap. Flux gates were drawn approximately perpendicular to flow direction based on the orientation of medial moraines, structural patterns of other surface-flow features, and/or of valley walls. We used the x and y component velocity observations to adjust the flux gate width such that the entire width of all flux gates were perpendicular to flow4. Flux gates were subdivided into ~25 m segments (hereafter flux gate segments) using a unique orthographic coordinate system for each glacier to minimize the effect of distortion from regional projections. We then used these points to extract values from the velocity and ice thickness datasets.We drew 5016 km of flux gates manually, although after correcting fluxgate width to be perpendicular to flow the total length is 3802 km Table . If no tAf; Gt a−1, defined as positive here) from the ice discharge rate  across a flux-gate close to the glacier terminus and the mass change rate associated with terminus position change :−3)37, N is the total number of flux gate segments along the flux gate, n 37, 2; area shown in Fig. −2 a−1; defined as positive here).The velocity, ice thickness, and area change measurements were combined to derive mean frontal ablation rates for every glacier in the Northern Hemisphere over the periods 2000–2010 and 2010–2020. We computed the frontal ablation rate (2) of the glacier that is now replaced by the ocean for retreating glaciers, or which occupies previous ocean area for advancing glaciers (division by 2 is necessary to account for the average area over the decade as no area was lost at the start of decade), and is computed from the digitized termini positions in 2000, 2010, and 2020  and a glacier in the De Long Islands (10 km2), we could not generate reliable velocity results, and thus assumed a 5 ± 5 m a−1 velocity based on evidence of little ice motion . For Svalbard and the Russian Arctic, where the optical velocity record from 2000 to 2010 was sparse in ITS_LIVE, we filled this gap using 1992–2012 observations from the JERS1, ERS1, ALOS PALSAR, and TerraSAR-X satellites. We used synthetic-aperture radar (SAR) offset-tracking to compute winter velocity from these scenes at 100 m resolution43. We combined all available velocity observations over each decade to derive a mean decadal velocity along the flux gate for each glacier. We do not account for seasonal variability in ice motion due to a lack of data to quantify this variability. In the few instances for which no velocity data was available for the 2000–2010 period (3.9% of flux gates), mean decadal values from 2010 to 2020 were used to fill the gaps.Ice surface velocities were primarily derived from Landsat-based, annual displacement mosaics of the Inter-mission Time Series of Land Ice Velocity and Elevation  is distance from the glacier margin and W2 (m) is distance from the glacier centerline with thickness Hcenter (m). We use 10 m as a minimum ice thickness on the glacier margins. Similar approaches can be found in Sánchez-Gámez and Navarro54. This may not accurately reflect the glacier thickness if the centerline observation is not the deepest point on the glacier, or if the glacier valley is not U-shaped, although we have no way to quantify this.Direct radar-derived measurements, primarily from the Glacier Thickness Database (GlaThiDa) 3.0.355 , 161 have at least 75% coverage across the flux gate, and 120 have at least 90% coverage across the flux gate. When no thickness observations were available, data gaps were filled with modeling results from Millan et al.55 Fig. . We foun55 and flow-law theory37 to estimate the thickness.For five small glaciers where no modeled thickness data were available, we assigned a similar thickness to that of a morphologically similar nearby glacier. For small glaciers, modeling occasionally produces ice thickness values that are unrealistically small . When the model results suggested that the average ice thickness along the flux gate is <30 m, we replaced these values with 30 m and assigned an uncertainty of 20 m (for 144 glaciers during 2000–2010 and 230 glaciers during 2010–2020). For the six marine-terminating glaciers on Jan Mayen we used scarce point measurementsTo determine mean ice thickness t}H¯ Eq.  over theTo determine term Eq.  for the 56 to model the climatic mass balance 1. PyGEM assumes the basal mass balance and internal ablation is negligible. We calibrated PyGEM using geodetic mass balance estimates9. We used monthly ERA5 air temperature and precipitation data57 to compute glacier melt with a degree-day model, accumulation with a temperature threshold, and refreezing from annual air temperature. We extracted 58, and for Basins 2 and 3 of Austfonna, Svalbard 59. For glaciers lacking appropriate input data , we used regional (defined by RGI primary regions) averages of the climatic mass balance.To account for mass changes unrelated to frontal ablation  between the flux gate and glacier front), we used the Python Glacier Evolution Model (PyGEM)−1 (2000–2010) and 0.54 ± 0.46 Gt a−1 (2010–2020) of ice discharge, accounting for 2% of total ice discharge during both time periods. See Dataset For 490 glaciers from 2000 to 2010 and 602 glaciers from 2010 to 2020, the absolute 27 viewed from satellite imagery and literature where available64.We individually examined glaciers that exhibited a terminus advance from 2000–2010 and/or 2010–2020 to determine if the advance was due to a dynamic instability such as pulsing or surging. We classified the glaciers according to the RGI classification scale  based on glacier morphology −1, so we artificially increased discharge to be within the uncertainty of terminus change while assigning 100% uncertainty to the discharge. These adjusted glaciers accounted for a total frontal ablation of 0.02 Gt a−1.For the Nathorstbreen system and an outlet of the Leningradskiy Ice Cap, our measured discharge was greater than terminus mass gain. However, we adjusted these totals within their uncertainties to make physical sense. For six glaciers from 2000 to 2010 and one from 2010 to 2020, the discharge was less than the terminus change; however, in each instance the mass held in terminus advance was <0.02 Gt a1 of 362.5 × 106 km2. To account for mass changes below sea level that do not contribute to sea-level change as the ice displaces ocean volume, we subtract the mass losses due to retreat below sea-level or add the gains due to advance. Since the ice fraction of total ice thickness below sea level is unknown, we calculate a higher bound scenario (assuming a fraction of 90% which corresponds to ice close to flotation) and a best estimate lower-bound scenario (50%). Estimates of mass loss below sea level are typically excluded from current global mass balance estimates9. Our frontal ablation estimates alone are not able to provide a total sea level rise estimate because frontal ablation is only one component of mass balance.We estimated the sea-level equivalent of frontal ablation assuming a global ocean area37, We estimate the uncertainty in ice discharge entclass1pt{minimaWe relied on the uncertainties reported by each dataset, whether at the scale of a flux gate point, flux gate, or glacier to propagate the uncertainties through Eqs. 55, after accounting for elevation changes9 and debiasing . The SAR-derived velocity uncertainties average 10 m a−1 for TerraSAR-X and ALOS PALSAR43, 20 m a−1 for JERS-165, and 40 m a−1 for ERS66. We derived the uncertainty in flow direction based on the stated uncertainties in the x and y velocity products, translated into a flux gate segment width uncertainty At flux gate points, we found good agreement (<50% difference) between the average velocity uncertainties 53. When a model depth or thickness observation in the terminus region was not available to calculate terminus mass change, we assumed that the average thickness of the area gained or lost is 60 ± 30% of the average flux gate thickness.Unless otherwise reported, we assumed a 10% uncertainty in ice thickness 67.The uncertainty in area gained or lost 68 forced with ERA5 air temperature and precipitation57 calibrated on 2000–2019 glacier mass balances9 for each glacier. We assumed the uncertainties in climatic mass balance are independent between glaciers.We estimated the uncertainty in the climatic specific-mass balance from the median absolute deviation of 50 simulations from Bayesian calibration of model parameters70 using the difference between independent sources of estimates at the same flux gates. We performed the spatial correlation analysis at distances covering several orders of magnitude (from 25 m to 1000 km), thereby accounting for biases at glacier and regional scales through long-range correlations9.We quantified the spatial correlation of velocity and ice thickness uncertainties (Supplemental Fig. We compared ITS_LIVE and MEaSUREs velocity observations in Greenland (Supplemental Fig. 55 (Supplemental Fig. We compared all available ice thickness measurements to debiased model estimatesMore details on spatial correlations are available in the Supplementary Material.For the ice discharge uncertainty Eq. , we indementclass2pt{minim71:We propagated the uncertainties in ice discharge at the flux gate from flux gates For the terminus mass change uncertainty, we applied a similar approach to propagate the uncertainty in average ice thickness over the area gained or lost Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Data 1


Staphylococcus pseudintermedius (MRSP) infection of any type, dogs may continue to carry MRSP asymptomatically on skin and mucosae, contributing to the spread of this multidrug‐resistant, veterinary hospital‐associated pathogen with zoonotic potential to others and into the environment.Following recovery from meticillin‐resistant This study determined which canine anatomic and household environmental sites are most sensitive for sampling to identify carriage and contamination.Fifty‐one dogs and 22 households, MRSP‐positive on at least one tested site, were sampled on 132 and 40 occasions over time, respectively. Dogs were swabbed at six sites ; household environments were sampled using contact plates  on five sites. MRSP was isolated after enrichment, grown on MSA/MS+ and was confirmed by PCR. Generalized estimating equations were used for calculation of sensitivity  for each site/combination.Each anatomical and environmental site yielded MRSP at least once. MRSP was isolated from only a single site in 27.3% of dogs, with the buccal mucosa showing the highest sensitivity (63.8%). Multi‐site sampling of a minimum of four canine anatomical or four environmental sites, respectively, was needed to achieve >95% sensitivity.The canine buccal mucosa should be included in MRSP sampling protocols, ideally in addition to at least three other anatomical sites. Likewise, environment sampling should be of multiple household sites in cases where it is used as a part of clinical case management. Background – Following recovery from meticillin‐resistant Staphylococcus pseudintermedius (MRSP) infection of any type, dogs may continue to carry MRSP asymptomatically on skin and mucosae, contributing to the spread of this multidrug‐resistant, veterinary hospital‐associated pathogen with zoonotic potential to others and into the environment. Objectives – This study determined which canine anatomic and household environmental sites are most sensitive for sampling to identify carriage and contamination. Conclusions and clinical relevance – The canine buccal mucosa should be included in MRSP sampling protocols, ideally in addition to at least three other anatomical sites. Likewise, environment sampling should be of multiple household sites in cases where it is used as a part of clinical case management. CIconfidence intervalGEEgeneralised estimating equationsMDRmultidrug‐resistantMRSAStaphylococcus aureusMeticillin‐resistant MRSPStaphylococcus pseudintermediusMeticillin‐resistant MS+Mannitol salt agar supplemented with 6 mg/L oxacillinMSAMannitol salt agarMSSPStaphylococcus pseudintermediusMeticillin‐susceptible PCRPolymerase chain reactionRVCRoyal Veterinary CollegeTSBTryptone soy brothStaphylococcus pseudintermedius (MRSP) has become the major multidrug‐resistant (MDR) bacterial pathogen in canine skin and soft‐tissue infections.Staphylococcus aureus infections,Over the past 15 years, meticillin‐resistant Screening for MRSA carriage in humans before hospital admission or elective procedures is routine worldwide, within the boundaries of funding and practicability. Systematic review indicates that the most sensitive single human swabbing site is the nose, detecting 68% of carriers (34%–91%),S. pseudintermedius carriers (16%–64%), with the perineum and mouth cited as predominant carriage sites.S. pseudintermedius (MSSP), with perineal (63%) and corner of the mouth (58%) sampling being most sensitive.Conversely, nasal swabbing in dogs is reported to be less sensitive than in humans to identify The household environment has been highlighted for potential contamination by MRSP‐carrier dogs, providing a source for future reinfection. Previous studies identified MRSP most commonly in dog‐accessible areas, such as feeding and sleeping places.Previous sampling studies for MRSP carriage in dogs have focussed on the nose and perineum, extrapolated from nasal swabbing for human MRSA carriage, and ease of sampling the perineum. This study aimed to determine the sensitivity of swab sampling six anatomical sites for detecting canine MRSP carriage, and sensitivity of contact plate sampling of five household environment sites for environmental contamination.This study was approved by the Royal Veterinary College's (RVC) Clinical Research Ethical Review Board (URN 2012 1166); owners gave written consent at enrolment.Dogs had been recruited as part of a study investigating the efficacy of topical antimicrobial therapy for eradicating MRSP carriage after a previous episode of MRSP infection had resolved. They had been enrolled either at the Queen Mother Hospital for Animals (RVC) or via referring veterinary surgeons between May 2016 and December 2019.Six anatomical sites were sampled from each dog: buccal mucosa inside the upper lip, outside the teeth; nose including nasal planum and one or both nostrils; conjunctival mucosa uni‐ or bilaterally; axilla or groin skin; preputial or vulval mucosa; and perianal area where nonhaired meets haired skin. Dry sterile cotton swabs  were rolled over each site for 3–5 s.For household contamination, five different sites in the room most frequently occupied by the dog were sampled: floor; frequently cleaned hard hand‐touch surface (e.g. kitchen work surface); infrequently cleaned inaccessible surface (e.g. top of cupboard); dog bed; and dog bowl. Owners were instructed to place paired mannitol salt agar  and MSA supplemented with 6 mg/L oxacillin (MS+) 55 mm contact plates (ThermoScientific) on each site for 5 s.‘Sampling event’ was used to describe each time at which a full set of samples  was taken.Swabs and plates were posted to the RVC for microbiological analyses and processed immediately on receipt. Swabs were incubated individually in tryptone soy broth  supplemented with 10% sodium chloride (Sigma‐Aldrich Ltd) at 37°C for 48 h. Broth aliquots were subcultured onto MSA and MS+ and incubated at 37°C for 24–48 h. Contact plates were incubated at the laboratory at 37°C for 48 h. If no growth was observed after 48 h, the sample was discarded.nuc, and mecA.Each distinct, presumed staphylococcal, colony from MSA and MS+ was subcultured onto blood agar base  containing 5% sheep blood (TCS BioScience) after morphological assessment based on size , shape (round with regular edges) and colour (white to cream) of colonies. Growth was further characterized phenotypically for clumping factor ability using dog plasma, DNase production and by Voges‐Proskauer testing.p ≤ 0.05 (Spss Statistics v26).Results of sampling events were analysed for dogs/environments testing positive for MRSP at a minimum of one site. Generalized estimating equations (GEE), accounting for repeated measures of some dogs or environments, were used to determine sensitivity  of each site, and combinations of sites, in detecting MRSP . GEE used dog or environment as the subject variable, with an exchangeable working correlation matrix in a binary logistic regression model. Comparison of sensitivity of single sites used the same GEE with site included as a linear predictor, significance One‐hundred thirty‐two sampling events from 51 dogs (≤12 repeated samples from the same dog) and 40 sampling events from 22 household environments (up to four repeated samples from a single environment) were available for analyses  sampling events (24 of 51 dogs). In 16 of 132 (12.1%) sampling events, all six swabs yielded MRSP (13 of 51 dogs). The buccal mucosa most frequently yielded MRSP (Table p < 0.0005) or prepuce/vulva (p = 0.008). Nose, conjunctiva and prepuce/vulva were significantly more likely to yield MRSP than axilla/groin skin . No other significant differences were seen. To achieve sensitivity ≥95%, at least four sites needed to be swabbed, always including both buccal mucosa and nose (Table Meticillin‐resistant p = 0.037) and infrequently cleaned area (p = 0.003), and the bed, bowl and floor were more sensitive than the frequently cleaned site . A sensitivity ≥95% was achieved only by combining at least four sites: the dog's bed, bowl, floor and infrequently cleaned site  of sampling events (17 of 22 households), and none yielded MRSP from all sites at the same time. MRSP was most frequently recovered from the dog's bed .Although not investigated in this study, pooling samples from different sites for processing where only a binary outcome report of MRSP carriage is needed, may be considered to reduce cost. Comparable results (93%–97% agreement) to individual culture have been reported for pooled MRSA swab processing,For environmental sampling, best sites remain uncertain. Although all sites yielded MRSP at least once, the dog bed showed a moderate sensitivity of 55%, while yield from other sites was comparatively low. ‘Hand‐touch areas’ in human medicine have been identified as preferred sampling sites owing to their importance in MRSA‐transmission.In conclusion, buccal mucosa, nose and at least two additional sites should be swabbed to maximize detection of MRSP carrier dogs. Overall, these findings should be incorporated into veterinary infection control protocols to minimize the impact of canine MRSP carriers within the veterinary practice through accurate detection.Sian‐Marie Frosini: Conceptualization; formal analysis; investigation; methodology; writing – original draft; writing – review and editing. Ross Bond: Conceptualization; funding acquisition; investigation; methodology; writing – review and editing. Ruth H King: Investigation; writing – review and editing. Anette Loeffler: Conceptualization; funding acquisition; investigation; methodology; writing – original draft; writing – review and editing.SMF and this study were funded by a Biotechnology and Biological Sciences Research Council  industrial CASE scholarship in partnership with Dechra Veterinary Products Limited .Design of the study; collection, analysis, and interpretation of data; and writing the manuscript, were undertaken independently of the funding body.Table S1Click here for additional data file.


To evaluate the effect of three-dimensional virtual pre-operative planning (3DVP) on the incidence of dorsal screw penetration after volar plating of distal radius fractures.A cross-sectional diagnostic imaging study was performed. Twenty out of 50 patients were randomly selected from our index prospective cohort (IPC): a prior study evaluating dorsal tangential views (DTVs) in reducing dorsal screw penetration in internal fixation of intra-articular distal radius fractures using post-operative CT scans to quantify screw protrusion. Pre-operative CTs from this cohort were now used for 3DVP by three experienced orthopaedic trauma surgeons (supplementary video). 3DVP was compared with the corresponding post-operative CT for assessing screw lengths and incidence of dorsal penetration. The Wilcoxon Signed Ranks test was used to compare screw lengths and the Fishers’ exact for incidence of penetration.p < 0.001). The number of penetrating screws was 5% (13/273 screws) in the 3DVP group compared to 11% (10/91 screws) in the IPC (p = 0.047). Corresponding to a reduction in incidence of at least one dorsally penetrating screw in 40% of patients in the IPC group, to 18% in the 3DVP group (p = 0.069).Three surgeons performed 3DVP for 20 distal radius fractures and virtually applied 60 volar plates and 273 screws. Median screw length was shorter in the 3DVP when compared to IPC: 18 mm  versus 20 mm   may reduce the incidence of dorsally penetrating screws in patients treated with volar plating for intra-articular distal radius fractures. II, diagnostic imaging study.The online version contains supplementary material available at 10.1007/s00068-021-01800-2. Tenosynovitis and rupture of extensor tendons due to iatrogenic dorsal screw penetration have been reported as complications after open reduction and internal fixation of distal radius fractures with use of a volar plate –8. StratIn recent years, three-dimensional virtual pre-operative planning (3DVP) has become increasingly available to orthopaedic trauma surgeons –16. HoweWe therefore conducted a cross-sectional diagnostic imaging study on 3D virtual pre-operative planning for intra-articular distal radius fractures to answer the main study question: does pre-operative 3DVP result in an additional reduction of dorsal screw penetration? Pre-operative Computed Tomography (CT) scans from our index prospective cohort  (IPC) weIn accordance to the Declaration of Helsinki, we retrospectively randomly selected (computerized) 20 patients from our index prospective trial  (IPC) ofThe index prospective cohort (IPC) study , comprisFor the purpose of our current diagnostic imaging study, 20 patients ) were randomly selected (computerized) from our previous study. The available pre-operative CT scan of each patient was used to perform 3DVP. Subsequently, 3DVP was compared with the corresponding post-operative CT scan of the index procedure to assess potential differences in number of dorsal screw penetrations  performed a series of virtual open reductions and internal fixations with volar plates on distal radius fractures from pre-operative scans of 20 patients using 3DVP software  (supplementary video). All observers in this study were blinded for screw lengths and plate size of the index procedure. 3DCT models of the distal radius were constructed from standard preoperative thin slice (< 1 mm thickness) CT scans. Subsequently, fracture fragments were aligned and reduced by virtually manipulating individual fragments in a three-dimensional space using drag-, tilt- and rotation-tools until a satisfactory anatomical reduction was obtained  3th compartment, (3) Lister’s tubercle, (4) 2nd compartment on the radial side, and (5) radial styloid. 3DVP was compared with the original IPC in terms of: total screw length, residual length between tip- and dorsal cortex; or length of cortical breach. In addition, appropriate screw lengths (yes/no) were defined as within 75–100% of distal radius diameter [Screw direction in degrees (within the 15-degree angle limitation of variable angle locking screws) and screw lengths (in 2-mm increments) were documented in millimeters for all screws. Screw lengths planned using 3DVP, were compared to the corresponding screws on the post-op CTs from the IPC Fig. a–d. In adiameter .Fig. 4a Statistical analyses were performed using the IBM SPSS software . The Wilcoxon Signed Ranks test was used to compare the ratio values; overall and individual screw lengths of the IPC versus 3DVP. Fishers’ exact test was used to compare percentages of dorsal screw penetration and appropriate screw lengths between 3DVP versus IPC. The Interclass Correlation Coefficient (ICC) was used to determine the inter-surgeon agreement on overall screw lengths. The ICC is scored in a 0 to 1 scale in which 0 means no correlation and 1 means perfect correlation. The Fleiss’ Kappa was used to determine the agreement between the three observers for the nominal value plate size. Pre-hoc Power Analysis  revealed that 20 consecutive patients were required to show a significant decrease in incidence of dorsal screw penetration from 40 to 0% with a power of 85% and an alfa of 0.05.After routine use of intra-operative DTV in our historical index prospective cohort , the totPositions of the ten dorsally penetrating screws were as follows; one screw was situated in the most ulnar position , one screw in the second most ulnar screw position , one screw was found to be penetrating in the central—Lister’s Tubercle—screw position (in plates with five holes), four screws in the second most radial position  and three screws were situated in the most radial position . Additionally, 1 out of 91 screws was found to be placed intra-articular in this series .Three experienced orthopaedic trauma surgeons virtually reduced 20 distal radius fractures selected from the IPC, and placed in total 60 volar plates and inserted 273 screws in the most distal row of the plate (6- or 7-head holes) in 20 unique patients in three independent rounds, using 3DVP software .p < 0.001). However, the number of screws of appropriate length was similar between groups: 81% (222/273) for the 3DVP group versus 86% (78/91) for the IPC (p = 0.427).The median screw length chosen in 3DVP setting was significantly shorter compared to the actual screws used in our IPC: 18 mm  3DVP group versus 20 mm  IPC (p = 0.047). This corresponds to a reduction in incidence of at least one dorsally penetrating screw in 40% (8/20 patients) in the IPC group, to 18% (11/60 plannings) in the 3DVP group (p = 0.069). A comparison of screw lengths per screw hole from ulnar to radial between IPC versus the 3DVP cohorts is presented in Table The number of penetrating screws was 5% 13/273 screws) in the 3DVP group compared to 11% (10/91 screws) in the IPC , 9% (7/91) and 1% (1/91)  was used. Inter-surgeon reliability for 3DVP plate size was fair   on the incidence of dorsal screw penetration after volar plating of distal radius fractures. This study demonstrated that 3DVP planned screw lengths were significantly shorter, as compared to the corresponding screws that were placed in clinical practice in our index prospective cohort  (IPC). SThis study should be interpreted in the light of strengths and weaknesses: major strength includes evaluation of 3D virtual pre-operative planning software as applied to a factual clinical scenario by experienced orthopaedic trauma surgeons . In contrast, in studies to date in orthopaedic trauma the segmentation and planning was mostly executed on locally developed software limiting the external validation of these applications. Limitations of this study include its retrospective design with limited number of patients, need of a CT scan which may not be appropriate in more simple distal radius fractures, selection bias due to inclusion of complex intra-articular fractures only and the fact that at this stage in development 3DVP is 30 min after the initial learning curve.The incidence of dorsal screw penetration was not reduced to zero. This may result from slight differences between the virtual reductions versus the actual post-operative reduction as observed on CT. Although, in our series all postoperative CTs from the IPC were reassessed and the intra-operative reductions were nearly as good as 3DVP reductions. Moreover, (a) the variable angle chosen (within limit of 15 degrees) in the 3DVP may deviate from the angle chosen in clinical practice in the original IPC, which could not be anticipated for due to the retrospective study design; and (b) actual plate position in the IPC may have differed from volar plate position when virtually planned. The relative importance of these factors need to be studied prospectively to further discover pearls and pitfalls of 3DVP in planning of complex trauma cases.3DVP has the potential to further optimize preoperative preparations in orthopaedic trauma care. Inter-observer agreement for screw lengths (ICC of 0.770) in this study, is comparable to the ICC (0.860) reported by Yoshii et al. . AlthougFrom an educational and resident training perspective, 3DVP allows surgical trainees to accurately plan the surgery ahead of time, to visualize his/her operative steps and strategy, and to subsequently discuss with a senior. Ultimately performing the surgery according to the discussed plan, increasing the efficacy of in-theatre hands-on learning in an era where operative time for residents is increasingly scarce –23. ReceA critical question however is how to convert a perfect 3DVP into a successful operation. Although this is topic of further research, we recommend showing the 3DVP planning on a screen in the operating room, with clear indication of the position and length of each individual screw. Adding a 3D print of the construct created in 3DVP could further facilitate the translation to clinical practice.3DVP may further decrease the incidence of iatrogenic dorsal screw penetration after volar plating of distal radius fractures. Prospective studies are warranted to evaluate the accuracy of translating the preoperative 3DVP to the operative procedure itself, preferably in a randomized control trial.Supplementary file1 (MP4 15378 KB)Below is the link to the electronic supplementary material.


Field observations of chlorophyll a and pheophytin (degraded and oxidized chlorophyll products) were used to calculate pheophytin proportions, i.e., (Pheophytin/(Chlorophyll a + Pheophytin)) and empirically determine whether the bloom was growing or mature based on remotely sensed bloom stages. Data collected at 13 north Bering Sea stations each July from 2013–2019 supported a pheophytin proportion of 28% as the best empirical threshold to distinguish a growing vs. mature bloom stage. One outcome was that low vs. high sea ice years resulted in significantly different pheophytin proportions in July; in years with low winter-to-spring ice, more blooms with growing status were observed, compared to later stage, more mature blooms following springs with abundant seasonal sea ice. The detection of growing blooms in July following low ice years suggests that changes in the timing of the spring bloom triggers cascading effects on mid-summer production.Decreased sea ice cover in the northern Bering Sea has altered annual phytoplankton phenology owing to an expansion of open water duration and its impact on ocean stratification. Limitations of satellite remote sensing such as the inability to detect bloom activity throughout the water column, under ice, and in cloudy conditions dictate the need for shipboard based measurements to provide more information on bloom dynamics. In this study, we adapted remote sensing land cover classification techniques to provide a new means to determine bloom stage from shipboard samples. Specifically, we used multiyear satellite time series of chlorophyll  An unprecedented lack of winter sea ice led to open water conditions throughout the winter of 2017–2018 in the northern Bering Sea . At leasSea ice is an important controlling factor for many of the biological characteristics observed on the Bering Sea shelf . Declinea biomass, and combine these data with comparable satellite observations to offer a potentially more synoptic identification of mid-summer bloom patterns.While other studies have evaluated the impacts on phytoplankton phenology from sea ice cover reductions in the fall  and spria observations from satellites have routinely been used to monitor surface phytoplankton bloom phenology, e.g.  [a from a previous bloom or if it followed a more prolonged unproductive state.Estimates of the life stage of the in-situ sampled bloom were determined using the proportion of pheophytin in the combined surface chlorophyll phytin)]  of fieldphytin)] . The No The impact of spring sea ice on mid-summer phytoplankton phenology was analyzed for each station year based on high and low ice years, which were defined by sea ice breakup dates and daily sea ice concentrations. Springtime sea ice concentrations were considered in addition to sea ice breakup dates to account for instances in which ice recovered and limited light penetration into the sea surface which may have obstructed photosynthesis and therefore bloom growth. Daily sea ice data were obtained from the Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager/Sounder (SSMIS) passive microwave instruments carried on Defense Meteorological Satellite Program satellites. Sea ice concentration estimates were calculated using the Goddard Bootstrap (SB2) algorithm , 39 at 2a concentrations. Therefore, surface (5 m) and depth-integrated chlorophyll a and pheophytin concentrations measured at each station were used to investigate the impact of high and low sea ice years on pheophytin proportions throughout the water column. The samples were binned according to low and high ice years and Welch’s t-test was used to compare the two groups to determine if their averages were significantly different from one another. The statistics were performed using the “numpy” and “scipy” packages in the Python programming language  [Pheophytin proportions determined from water column field samples as described above were grouped based on high and low sea ice years to investigate the impact of low sea ice on subsequent bloom phases in July. Depth-integrated pheophytin proportions were considered in addition to surface samples due to decreased sensitivity to wind-driven mixing and rapid nutrient depletion at depth compared to surface chlorophyll on.org/) , 45.a value every 25 days and a minimum of three chlorophyll a values between DOY 174–219). The excluded data were from BCL-6A and all DBO1 stations in 2013, as well as SLIP-1, SLIP-2, and SLIP-3 in 2018  except for surface samples binned using the timing of sea ice breakup date  from field measurements could be used to estimate bloom stage at the time of sampling based upon a satellite time series. To the best of our knowledge, this is the first application of this approach of basing remotely sensed classes on relation in time (growing or declining chlorophyll blooms) rather than direct snapshots of Earth’s surface to study the seasonality of phytoplankton growth stages. This application is based on the adaptation of remote sensing land cover classification techniques (e.g. [The classification methodology used here sought to determine if pheophytin proportion (the ratio of pheophytin to combined pheophytin and chlorophyll es (e.g. ) to clasa time series to estimate time-based classes, similar studies were unavailable for comparison. However, the overall accuracy of our classification model was 75%, which is consistent with previously published satellite-derived land cover classifications maps .Examination of the misclassified station years revealed a general pattern. Each of the remotely sensed (RS) EB that were field-classified as PB contained large pheophytin proportions, ranging from 29–61%. These instances occurred as a second bloom following a recently ended bloom . Therefore, the growing second bloom observed by satellite could not be distinguished in field samples due to elevated levels of pheophytin that remained in the water column from the preceding bloom. When considering the exact station matchups per year , the phea biomass, and do not necessarily incorporate a confirming at-sea measurement. Furthermore, in order to take advantage of several years of useable data, our remote sensing time series included an expansion of the minimum observations criteria to once in at least every 25 days rather than once in 20 days that was used in prior work in this region [Another limitation existed in using satellite observations as a reference because these data are also a proxy for surface level chlorophyll s region , 31. How2 = 0.94, p< 0.01). EB were more prevalent in later years (2016–2019), yet the variability was reflected well in both models. Considering the satellite-derived bloom stages as the reference for individual matchups . Unfort5 in Roy  observed5 in Roy . Additio5 in Roy  found sea, pheophorbide a, and pyropheophorbide a) to be > 1 at the majority of their Chukchi Shelf stations for surface sediment concentrations, indicating viable cells. Goñi et al. [On the Chukchi Shelf, Goñi et al.  found boi et al.  reportedi et al. , the Juli et al. .p<0.05) in three of four analyses, although surface samples grouped by sea ice breakup of low and high years were not significant. The surface samples analyzed according to sea ice breakup had the smallest difference in mean (0.05) and nearly exact standard deviation (difference of 0.01) between the low and high ice year groups, which likely resulted in the insignificant distinction among them. Still, in most of the cases high versus low sea ice years produced statistically different outcomes for the observed pheophytin proportions.Pheophytin proportions differed between high and low ice years for samples collected at the surface as well as depth integrated inventories. These data provided consistent evidence of a connection between the timing of sea ice dissolution and pheophytin proportions . High sea and pheophytin proportions  bloom stage that is typical in high sea ice years. Prior work on these dynamics, e.g. the Oscillating Control Hypothesis [a biomass extending into mid-summer. In short, the detection of this phase shift with increased observations of EB rather than PB conditions in low ice years suggests that changes in timing of the spring bloom further alters mid-summer production.Results of our classification model indicate it is practical to define bloom stage based on pheophytin proportion relative to chlorophyll pothesis  projectepothesis . Althouga concentrations within a late spring bloom (with onset on approximately June 12) in 2018 owing to the lack of fresh water input from melting sea ice resulting in weak stratification [Other observations simultaneous with our study include the M5 mooring southeast of St. Matthew Island in the Bering Sea, where observations were made of low chlorophyll fication  also obsfication  of laterThe absence of winter sea ice in the Bering Sea in 2018 could become typical by the 2040s . Based oa pigment inventory to distinguish growing blooms from post-peak bloom stages. Our study found that samples that consisted of less than 28% pheophytin proportion represented growing blooms while proportions higher than 28% indicated past peak or senescent blooms according to remotely sensed chlorophyll a phenology. Although additional studies are needed to confirm this model with other northern Bering Sea datasets, our results suggest that pheophytin proportions can be used as a proxy for bloom stage as confirmed by satellite sensed phenology.The classification model presented is shown to be able to resolve phytoplankton growth stages within bloom cycles from in-situ discrete water samples. An optimized model for northern Bering Sea field samples produced a threshold of a proportion of 28% pheophytin in the overall pheophytin + chlorophyll p<0.05) for depth-integrated pheophytin. Surface pheophytin proportions were divided between two distinctive outcomes with high confidence (p<0.001) for March–May sea ice concentration. The increase in mid-summer EB signals observed in low sea ice years represents a shift from typical annual growth cycles. The Oscillating Control Hypothesis [Earlier sea ice breakup dates and reduced springtime sea ice concentrations led to a later spring bloom and subsequently an increase in early bloom stages (as opposed to matured blooms) being observed in mid-summer. The difference of pheophytin proportions from July cruise samples between high and low sea ice years was significant (pothesis  describeS1 Appendix(DOCX)Click here for additional data file.S1 TableThe sea ice breakup dates are expressed in Day of Year (DOY). Italicized dates are based on 2017 point location as a baseline because in situ samples were not gathered at the corresponding station.(DOCX)Click here for additional data file.S2 TableSampled surface chlorophyll, pheophytin, the associated portion of pheophytin relative to combined pheophytin and chlorophyll concentrations, and the classified life stage of the bloom according to satellite remotely sensed phenology at the DBO1 (top) and DBO2 (bottom) stations. For the remotely sensed life stage categories, NaN = Not enough cloud-free satellite observations available to resolve annual phenology, EB = Early Bloom, PB = Post Bloom, NB = No Bloom. Surface chlorophyll and pheophytin are in units μg/L.(DOCX)Click here for additional data file.S3 TableThe sea ice breakup dates changepoint analysis results to determine the day of year (DOY) threshold to distinguish high versus low sea ice years within our study duration per station. These were derived using the methodology described in S1 Appendix.(DOCX)Click here for additional data file.S4 TableHigh and low sea ice years were distinguished using DOY thresholds determined per station based on sea ice breakup date (SIB) and by sea ice concentration (SIC) relative March–May coverage at each station during the 2013–2019 time period.(DOCX)Click here for additional data file.