Calotropis procera, Phyla nodiflora, Eclipta alba and Ranunculus sceleratus. It was found that most of the selected plants were phytoaccumulators, making them best suited to survive in harsh environments such as those with industrial pollution. The Fe concentration in the plant constituents was the highest, along with Zn, Pb, Cd, and Cu, all of which were above the permissible limits of the WHO. The metal transfer factor (MTF) was higher in most of the plants studied, and even exceeded 10 at some severely affected sites. Calotropis procera proved to be the most suitable plant for growth on drainage systems and also at river sites, as it had the highest importance value across all sites and seasons.Faisalabad is a major industrial area in Pakistan’s Punjab province that discharges wastewater into the Chenab River. Industrial effluents in Faisalabad are predicted to pose a significant threat to the riparian vegetation of the Chenab River and nearby vegetation. Heavy metal pollution of plants, water, and soils is one of the biggest problems worldwide that needs to be addressed because heavy metals above normal levels are extremely dangerous to both riparian vegetation and wildlife. The results indicated high levels of pollution in the industrial effluents as well as in the river in terms of salinity, metal toxicity, TSS, TDS, SAR, the acidic and alkaline nature of the industrial effluents, and the spread of industrial effluents up to 15 square kilometres in the Chenab River. Despite the higher pollution, four plants were found at all sites:  Riparian zones serve as a barrier between the aquatic and terrestrial environments. Riparian zones provide many ecosystem services, such as nutrient modification, erosion control and temperature regulation, which improve water quality in adjacent aquatic ecosystems .The textile industry is a major source of environmental pollution. In terms of environmental pollution, the textile processing industry tops the list. Although the industrial area of Faisalabad is the backbone of Pakistan’s economy, these industries consume a large amount of water and generate excessive wastewater. This wastewater is discharged without treatment into water canals, where it flows into the Chenab River .Heavy metals are the most prevalent pollutants in industrial effluents. One method of cleaning heavy metal contaminated soils is to use plants that have the ability to grow, adapt and absorb metals . The pH Calotropis procera compared to other plants, with concentrations as high as 188.2 and 68.2 mg/kg in shoots and roots, respectively  were selected to study water and soil parameters and metals in water, soil and plants of some dominant species. The polluted sites were selected within a radius of 500 m from the polluted area, while the unpolluted area was about 14 km away near the Chenab Nagar hills. While selecting the sites for plant collection, care was taken to minimize disturbance  to ensure the consistent accumulation of industrial pollutants at the plant sites.The study area consists of dry plains and a foothill, where the climate is dry and hot. The average maximum temperature in June was 48 °C and the minimum temperature in January was 4 °C . The climatic conditions in the study area fall under the warm desert climate (BWh) according to the Koeppen-Geiger classification. The average annual rainfall is 336 mm in Chiniot and 346 mm in Faisalabad.Calotropis procera, Eclipta alba, Phyla nodiflora and Ranunculus sceleratus) were collected from the selected sites and carefully brought to the laboratory for metal analysis. Water and soil samples were also taken at the 10 selected sites in four seasons.The roots, stems and leaves of selected plants  was performed and biplots were generated using Cano Draw v. 4.0 supplied with CANOCO for Windows version. 4.5.The experiment was conducted in a 2-factorial (collection areas and species) completely randomized design with six replicates. The means were compared using Duncun’s Multiple Range Test at a significance level of Water samples were collected from all three drains and seven different sites (one non-polluted) of the Chenab River during four seasons. The metal values are determined to check the heavy metal toxicity in the water samples. The samples were digested for heavy metal determination. The concentration of various metals in industrially polluted drains showed significant differences between the different polluted sites. The polluted sites received much higher effluents compared to the unpolluted control.The analysis of the physico-chemical properties of the effluents from ten sites revealed that the pH was highest in the Paharang drain. The data show that the pH was above 7 at studied sites. The electrical conductivity of the effluents differed either among the three drains or among the seven sites. The highest value of EC was recorded at the Paharang drain with a value of 48.27, followed by the Marah Chiniot drain and Ahmad wala drain with values of 47.38 and 45.24, respectively. The values of chemical oxygen demand (COD) and biological oxygen demand (BOD) differed greatly among the pollution levels and were high in three drains compared to the non-polluted and river sites .Ca+Mg concentrations were high at all drain sites in this study compared to river sites. The highest value of Ca+Mg ions was measured in the water samples from the Paharang drain. Sodium levels were excessive at all drains compared to river sites, with the highest enrichment found at the Paharang drain. Bicarbonate ions in the textile dye industry effluents were highest in the Paharang drain, as the Paharang drain contains most of the effluents from the industrial units. As a result of the dilution of industrial water by the Chenab River, lower bicarbonate content was measured at River Site 1 and at River Site 3. The amount of carbonate in the water samples was highest in the Paharang drain. The Parahang drain and Ahmad wala drain were rich in chlorides and carbonates, with maximum values of 34.64 and 34.37 respectively. The SAR and TDS maximum value was recorded in the Ahmad wala drain .The maximum Cd content was found at the Marah Chiniot drain at 0.218 ppm. The safe limits for Cd in effluents recommended by WHO are 0.003 ppm , while dThe highest Mn concentration was found in the Marah Chiniot drain at 0.064 ppm . On the The graphical data for the analysis of heavy metals from industrial effluents showed that the correlation factor between non-polluted and polluted sites was very high for documented metals except iron. The data show that heavy metals such as Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were present at all polluted sites in four seasons with the highest correlation, while the concentration of the metals in the same seasons was lower at non-polluted site. Studies showed that Cd concentrations were higher at polluted sites compared to non-polluted site in all seasons . MeanwhiData collected from the industrially influenced drains and river sites revealed that phosphorus levels were highest in the Paharang drain with value of 27.80, followed by the Ahmad wala drain and the least enrichment was recorded at River Site 4 with a concentration of 6.21. The amount of P was also found to be high in the Marah Chiniot drain. The analysis of soil samples from the area revealed that the amount of potassium was the highest in the Paharang drain with a value of 241.50, followed by the Ahmad wala drain. The saturation of the soil samples was highest at four different sites with no such changes, with a value of 42.0 at River Site 2, River Site 4, River Site 6 and River Site 7. The lowest saturation value was recorded in River Site 1 and River Site 3 .The soil potassium content was higher than the standard values (80 mg/kg) for K in the soil established by According to soil samples taken from various locations, the Ahmad wala drain has the highest levels of cadmium and chromium contamination. The Marah Chiniot drain exhibited considerable levels of Cd with 0.368 ppm and Cr 0.223 ppm respectively  & 3B. AcThe soil parameter results are more reliable for site selection because they include all sites, whether they drain water or not. When compared to other locations, the Ahmad wala drain graph for four seasons indicates a high amount of Pb and Ni  & 3G. MnGraphical data for the comparison of non-polluted site with three drains and six river-polluted sites clearly indicate that the concentration of metals in soil samples was higher in the polluted area compared to the non-polluted area, except for Fe and Mn. Iron showed variations compared to other metals, and iron concentration was higher at non-polluted site in four seasons compared to polluted river sites and drains . The metThe PCA biplot for the analysis of data for water and soil combined in March to early spring showed Site 2 on extreme with respect to the pH of water, potassium, EC of water, K, COD and saturation. Similarly, Site 5 was clustered close to organic matter, CO3, BOD, Cl, phosphorus and total dissolved solids.The biplot shows that the combined analysis of soil and water in the summer showed that the biplot data were similar in the summer and spring. CO3, Cl, EC of water, pH of water, Ca+Mg and TDS were present in the highest association with Site 5, while K was found in a highly associated state with Site 2. The biplot for the month of September, which is autumn, shows the same correlation as reported in spring and summer, and Site 2 had the highest correlation with the pH of the water and Ca + Mg ions. Potassium, Cl and CO3 were clustered close to Site 2, while the pH of water, organic matter, EC of water, phosphorus, BOD, and TDS were found to be associated with Site 5. Saturation showed an association with Site 10.The biplot for winter was different compared to the biplots for spring, summer and autumn. The data for winter show that EC of soil was associated with Site 10, while pH of water, saturation, Ca+Mg, and phosphorus were associated with Site 5. Site 2 was associated with K, TDS, EC (water) and pH of the soil. The results showed that the parameters of water and soil were on extreme in four seasons at ten different sites .In plant components (whole plant) of four ecotypes heavy metals such as Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn were checked in the three different drains and seven river sites (one non-polluted) throughout the four seasons of the year. The results suggest that the increased cadmium content in all selected plants was measured at the Ahmad wala drain. In plant components, the maximum contamination level of chromium was calculated at River Site 5, followed by the Paharang drain in four ecotypes. Among the plants under study, the highest mean value of Copper was calculated at the Ahmad wala drain. The highest content of iron was accumulated at the Marah Chiniot drain, followed by the Ahmad wala drain. The concentration of Mn was also reported highest in Ahmad wala drain. The maximum nickel value found at the Marah Chiniot drain was 0.665 ppm. The elevated Lead value was calculated at the Marah Chiniot drain at 0.727 ppm in the plants under study. The highest Zinc contamination level at the Ahmad wala drain was calculated to be 1.90 ppm .P. nodiflora at 0.161 ppm. The highest chromium concentration was also accumulated in P. nodiflora at 0.104 ppm. The concentration of copper was as high as 0.665 ppm in C. procera. Moreover, an elevated iron rate was measured in E. alba at 2.11 ppm. The maximum Mn contamination level was calculated in C. procera at 0.264 ppm. Nickel excess concentration was present in the components of R. sceleratus with value of 0.542 ppm. Similarly, the maximum lead concentration was determined in E. alba at 0.695 ppm in four seasons. Among the four ecotypes under study, the zinc concentration was observed at its maximum in P. nodiflora at 1.38 ppm and the lowest concentration was reported in C. procera at 0.81 ppm. Seasonal variations in heavy metal concentrations among the four ecotypes being studied were also significant  describes the bioavailability of heavy metals to plants. In the calculations for the soil-to-plant metal transfer factor (MTF) as the ratio of plants to metal concentration in soil, the following equation was used . \documl factor . The difl factor . The traC. procera, E. alba, P. nodiflora and R. sceleratus were noted for all ten sites, and the bioconcentration factor for Cd in this finding was greater than 1 in selected plants, which indicates efficient transfer of metals from soil to plants. The bioconcentration factor for chromium in the present finding was also greater than 1 in selected plants, which indicates efficient transfer of chromium from soil to plants. The value of the MT factor greater than unity indicates that plants can accumulate heavy metals, while the MTF less than unity showed that plants just absorb metal  was performed separately for each season and for each site to track the change in physiological and biochemical parameters and heavy metals on a spatial and temporal scale. Some physicochemical parameters such as TDS, Na and SAR were in high correlation with Site 9, which was plotted with Mn, Cu, Cd, Ni, Zn, and Fe. Similarly, most of the metals were highly associated with River Site 6 and Ahmad wala drain.The triplot for the month of June was much more complex than triplots for the month of March. In summer, the correlation was highly present at River Sites 4, 5 and 6 in the physiochemical parameters of water and soil, which were clustered at the centre, while metals such as cadmium and chromium were found in correlation with the Paharang drain, while metals like nickel and zinc were plotted in correlation with Site 6 and Site 9.Autumn showed much more variation compared to other seasons. Water and soil physicochemical parameters were present in association with Site 5 and Site 2. Similarly, Site 6 was plotted towards Zn and Cr mainly and showed some association with saturation of soil. Most of the metals were found in association with Sites 8 and 9. Heavy metals were highly correlated with Site 9 and showed some association with Site 2. Most of the physiochemical parameters for water and soil were plotted towards Site 8 and Site 2 .It was hypothesized that the three drains coming from Faisalabad industries carry polluted water. To test this hypothesis, soil and water samples were collected from the drains and river Chenab and subjected to different tests. High levels of pollution were recorded in both soil and water samples collected from the Chenab River and its associated drains. One site was selected as a non-polluted site before the entry of the first drain into the Chenab River.Among the attributes of the water being studied, pH did not vary significantly across the non-polluted site, drains and river sites. However, at drains pH of the water was higher, which can be attributed to the presence of pollutants in the drainage water from the Faisalabad industries, which are considered a major contributor to pollution. Drains along river sites are facing severe degradation in water quality because of industrial effluents. The water quality was relatively better at a non-polluted site 20 km above the first drain. Water quality was degraded from the Marah Chiniot drain point source to the Ahamd wala drain and its associated river sites (Sites 6-7) because of pollutants from drains. The electrical conductivity (EC) of water indicated a higher contamination level and pollution stress at all sites except River Site 1, a non-polluted site and Site 7, where river water flow was high. Such results were also reported earlier by Spatial variations in the water quality of drains and associated river sites were due to various parameters such as total dissolved solids (TDS), chemical oxygen demand (COD), biochemical oxygen demand (BOD), electrical conductivity (EC), and heavy metals like cadmium (Cd), chromium (Cr), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), potassium (K), phosphorous (P), sodium (Na), and zinc (Zn). It was reported that concentrations of all these metal ions in the drain effluents were above the recommended NEQS limits. The problem of pollution in the Faisalabad industrial polluted area has been reported previously by . HoweverThe contribution of parent rock material that was loaded with Fe, was evident in the concentration of Fe in the studied samples at River Site 1 Chenab Nagar, as Chenab Nagar is a mountainous area. A high level of pollution was confirmed at three drains and associated river sites. Such a high level of pollution in drains and rivers can be attributed to the locality of the area. This fact is also supported by the high EC of samples from drains and some river sites. The problem of industrial pollution from industrial areas has been reported previously by The analysis of soil included a non-polluted site, the pH of the soil did not vary much; however, the EC of the soil was high at the non-polluted site. On the other hand, saturation of the soil did not vary significantly across the selected sites. It was observed that the availability of organic matter was twice as high at drains compared to river sites and the concentration of phosphorus was also much higher at drains compared to river sites. The potassium value was also higher at drains and their associated sites compared to a non-polluted site. Higher content of organic matter and phosphorus at drains indicates the flourished growth of plants along the drains and associated river sites. The potassium concentration was also high at drains. The higher amount of these minerals indicates the higher vegetation density at these sites, which was noted in the second phase of the study. Among the heavy metals, the amount of iron was noted to be high at all sites along River Site 1, which showed the peak values of iron along the drains. At all sites studied, the amount of iron was the highest, followed by lead. The concentration of zinc was also higher at all sites, and its value was greater than 1 at all 10 sites. Their source has been described earlier, the drainage water from industrial pollution. The heavy metals come with industrial pollution drainage and can be deposited in soil or settle in the beds of drains. Such pollution has been reported by Keeping all the attributes under study in water and soil in view, and with the help of CCA and ANOVA both in soil and water, the major cause of pollution was found to be a problem of metals, followed by the spread of industrial pollution to large areas with the help of drainage from industrial areas and metal toxicity mainly due to lead, iron and zinc. The current study also suggests that drains were found to be a major contributor to the pollution at all sites except River Site 1.The study of soil and water in phase 1 revealed that among the commonly occurring heavy metals in industrial effluents, only lead, manganese, iron, nickel and cadmium were found in toxic amounts. Among these five metals, lead and cadmium, along with iron toxicity, were found at all sites, but lead and cadmium were not in toxic concentration at River Site 1, which was free from industrial pollution. However, the plants were tested for all eight metals to have any indication of hyperaccumulator species among the selected plants. For this purpose, the soil-to-plant metal transfer factor (MTF) was also calculated and was subjected to CCA to see if there was any association between the metals in the soil and plants.C. procera, E. alba, P. nodiflora and R. sceleratus were noted for all ten sites and the results suggest that the Cd concentration transfer factor in C. procera was present as high as 2.83 at River Site 3, followed by River Site 2 with value of 2.26, and the decreased level was noted at Site 2 with value of 0.09. In E. alba, the highest 8.75 MT was measured at River Site 3, followed by Site 3 at 7.00. Similarly, at Site 8, 1.32 TF was calculated, and the decreased concentration was noted at Site 8. The Cd contents in P. nodiflora were calculated to be greater than 1 at river sites 4, 6 and 7. In R. sceleratus, the cadmium concentration was as high as 12.00 at River Site 3, followed by Site 3 and the lowest at Site 8. The overall cadmium contents measured for TF were the highest at River Site 3 in all plants.Metal transfer factor for C. procera at Site 1 (10.31), while recorded lowest in P. nodiflora at Site 8. Overall, in all four plants , the value of chromium was higher than 1 and showed that chromium was accumulated in all these plants at all sites. The Cu measured in C. procera at Site 1 and Site 6 showed values greater than 1, while P. nodiflora and R. sceleratus at Site 1. Therefore, the value was higher at Site 1 and the lowest measured at Site 8 in E. alba. The bio-concentration factor for cadmium and chromium in the present findings was greater than 1 in selected plants, which indicates efficient transfer of metals from soil to plants The MT value for chromium was recorded highest in C. procera was found to be highest at Site 3 (0381) and lowest at Site 9. The MT measured for E. alba showed the highest value of Fe at Site 3 (1.788) and the lowest at Site 1. Similarly, P. nodiflora showed a peak of Fe at Site 3 (1.669) and the least value at Site 9 (0.375). The ecotype R. sceleratus showed the highest value at Site 3 (1.47) and the lowest at Site 8 (0.332). MTF measured for Mn was greater than 1 only in C. procera at Sites 4, 7 and 9, while it was lowest in C. procera at Site 10 as 0.075. Among the other three ecotypes, Mn was recorded below 1 at all study sites. The overall bio-concentration factor for Fe at some sites was greater than 1, indicating its greater availability to plants and lower retention in the soil. The metal transfer factor for the plants being studied was measured at all ten sites. A ratio of Fe to the metal transfer factor in R. sceleratus. The nickel’s highest value was calculated in R. sceleratus as 1.18 at Site 10 and the lowest in C. procera as 0.27 at Site 5. The TF for Pb calculated at all sites in all samples was measured lower than 1. Zn’s highest value for MT was reported at Site 4, as 1.03, followed by Site 10 as 1.01 in P. nodiflora, and the decreased in C. procera at Site 5. The results suggest that most of the plants under study were hyperaccumulators, as the value of MTF was higher than 1 in all plants at different sites for different metals.The value of an MT factor greater than unity indicates that plants can accumulate heavy metals, while an MTF less than unity shows that plants just absorb metal . Calculai.e., Calotropis procera, Phyla nodiflora, Eclipta alba and Ranunculus sceleratus) were found growing at all sites. However, phytoremediation by all studied plants has been identified as the most dominant, acclimatized species of the area that can be used for the revegetation and reclamation of industrial pollution.At the end of the study, it has been concluded that a significant level of pollution is present at the study sites of the River Chenab and the three associated drains carrying effluents from the industrial areas of Faisalabad, Punjab, Pakistan. The pollution is present in the form of high metal toxicity due to the presence of a large number of effluents along drains. Metal toxicity, especially the lead, iron, zinc, chromium, and cadmium toxicity, possibly due to effluents from the industries, was higher. The water and soil quality was degraded as the quantity of TSS, TDS, and SAR increased because of the large quantity of effluents from the Faisalabad industries flowing into an enormous area of drains and the river Chenab. Moreover, the study has revealed that industrial pollution, which is a major contributor to pollution, is severely damaging the native vegetation of the area. Despite higher levels of pollution, four plants (10.7717/peerj.15565/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.15565/supp-2Supplemental Information 2Click here for additional data file.10.7717/peerj.15565/supp-3Supplemental Information 3Click here for additional data file.10.7717/peerj.15565/supp-4Supplemental Information 4Water physicochemical parametersClick here for additional data file.10.7717/peerj.15565/supp-5Supplemental Information 5Soil physicochemical parametersClick here for additional data file.10.7717/peerj.15565/supp-6Supplemental Information 6soil and water combinedClick here for additional data file.


Multiple myeloma (MM) is blood cancer of plasma cells. Plasma cells are white blood cells, which are part of the immune system. Malignant plasma cells are found in the bone marrow and are difficult to treat. There have been many new therapies developed in recent years, but the disease is still considered incurable. Some of the treatments for MM are antibodies of the IgG class. We have developed a fully human antibody of another antibody class, IgE, targeting the CD38 molecule that is expressed on the surface of several cancers including MM. Our goal is to use the anti-CD38 IgE antibody to recruit different types of immune cells to kill malignant cells. In this article, we report that the antibody shows anti-cancer effects against MM cells. Thus, this IgE antibody should be further explored as a novel treatment for MM.Multiple myeloma (MM) is an incurable malignancy of plasma cells and the second most common hematologic malignancy in the United States. Although antibodies in clinical cancer therapy are generally of the IgG class, antibodies of the IgE class have attractive properties as cancer therapeutics, such as their high affinity for Fc receptors (FcεRs), the low serum levels of endogenous IgE allowing for less competition for FcR occupancy, and the lack of inhibitory FcRs. Importantly, the FcεRs are expressed on immune cells that elicit antibody-dependent cell-mediated cytotoxicity (ADCC), antibody-dependent cell-mediated phagocytosis (ADCP), and/or antigen presentation such as mast cells, eosinophils, macrophages, and dendritic cells. We now report the development of a fully human IgE targeting human CD38 as a potential MM therapy. We targeted CD38 given its high and uniform expression on MM cells. The novel anti-CD38 IgE, expressed in mammalian cells, is properly assembled and secreted, exhibits the correct molecular weight, binds antigen and the high affinity FcεRI, and induces degranulation of FcεRI expressing cells in vitro and also in vivo in transgenic BALB/c mice expressing human FcεRIα. Moreover, the anti-CD38 IgE induces ADCC and ADCP mediated by monocytes/macrophages against human MM cells (MM.1S). Importantly, the anti-CD38 IgE also prolongs survival in a preclinical disseminated xenograft mouse model using SCID-Beige mice and human MM.1S cells when administered with human peripheral blood mononuclear cells (PBMCs) as a source of monocyte effector cells. Our results suggest that anti-CD38 IgE may be effective in humans bearing MM and other malignancies expressing CD38. The plate was then incubated for 1 h at 37 °C. The reaction was terminated by the addition of sodium carbonate buffer  and absorbance at 405 nm was measured using a FilterMax F5 multi-mode microplate reader . β-hexosaminidase release in experimental samples is expressed as a percent of total content within the basophilic cells as determined by separate treatment with 1% Triton X-100 in phosphate-buffered saline (PBS). Statistical analysis was performed using Student’s t-test .This assay, based on β-hexosaminidase release into the culture medium, was performed as previously described ,25 with Since human IgE is not recognized by murine FcεRI nor FcεRII ,38,39,402 and 37 °C, or differentiated into macrophages and activated to express an M1 phenotype using ImmunoCult™-SF Macrophage Medium (STEMCELL Technologies) following the manufacturer’s instructions. Flow cytometric analysis of ADCC and ADCP was performed as described [6 cells per mL for 10 min as per the manufacturer’s instructions. Target cells were then washed and incubated in fresh growth medium at 5% CO2 and 37 °C overnight. The next day effector cells (IL-4 treated monocytes or M1 macrophages) and target cells were mixed together at a 5:1 effector to target ratio and incubated with 5 μg/mL of antibody in growth medium for 2.5 h at 5% CO2 and 37 °C in quadruplicate. Cells were then washed in growth medium and incubated with a PE-conjugated mouse anti-human CD89 antibody (BD Biosciences) for 25 min to identify phagocytes. DAPI  was added at a 1 μg/mL concentration to identify dead cells with cells treated with saponin used as a positive control for cell lysis. Samples were analyzed on a BD LSRII analytical flow cytometer, and 5 × 104 events were collected. CFSE+/PE+ cells designate ADCP events and CFSE+/DAPI+ cells designate ADCC events. Statistical analysis was performed using Student’s t-test .Monocytes were isolated from human peripheral blood mononuclear cells (PBMCs) obtained from healthy donors  using the EasySep™ Human Monocyte Isolation Kit . PBMCs were either treated with 10 ng/mL of recombinant human interleukin 4  in AIM-V serum-free medium (Thermo Fisher Scientific) with 5% FBS and incubated for 20 h at 5% COescribed  with mod137Cs, Best Theratronics, Ltd., Ottawa, ON, Canada) a day before xenograft implantation, and were implanted with 5 × 106 MM.1S human MM cells i.v. via the tail vein. On Day 1 and Day 7 post-implant, mice were treated i.v. with buffer (PBS) control, 100 μg anti-CD38 IgE, 5 × 106 PBMCs (as a source of monocyte effector cells), or 5 × 106 PBMCs combined with 100 μg anti-CD38 IgE. For the last treatment group, the IgE and PBMCs were added to the same tube and placed on ice until injections could be performed. PBMCs were obtained from healthy donors (UCLA CFAR Virology Core Laboratory). The PBMCs for each independent study were from separate donors. Mice were then observed for the onset of hind-limb paralysis (end point), and the number of days survived was recorded. Kaplan–Meier survival analysis was used to analyze the data and different Kaplan–Meier survival plots were compared using the log-rank test in GraphPad Prism, Version 9 .C.B-17 SCID-Beige female mice (8–12 weeks old), obtained and housed in the Defined Flora Mouse Facility in the Department of Radiation Oncology at UCLA, were exposed to whole-body sublethal irradiation of 3 Gy , PBMCs alone , or buffer . These results also show no difference in the survival of anti-CD38 IgE-treated mice versus buffer treated mice (p = 0.3343) and a slight, but significant, increase in survival in PBMC-only treated mice compared to buffer treated mice (p = 0.0457). The observation that mice given PBMCs alone survived longer than buffer controls is consistent with previous studies [We then sought to evaluate the potential antitumor effects of the anti-CD38 IgE antibody in a disseminated mouse model of MM. SCID-Beige mice treated with anti-CD38 IgE and human PBMCs as a source of monocytes (effector cells), survive significantly longer  and isatuximab (Sarclisa®), have benefited MM patients, especially when they are used in combination with other drugs [CD38 is a multifunctional type II transmembrane glycoprotein that acts as a receptor, an adhesion molecule interacting with CD31, and as an ectoenzyme (ADP-ribosyl cyclase/cyclic ADP-ribose hydrolase) ,43,44. Eer drugs . Unfortuer drugs , and thu®) and isatuximab (Sarclisa®) in MM has ignited enthusiasm to develop additional CD38-targeting agents. To take advantage of the unique properties of IgE antibodies as cancer therapeutics and to address unmet medical needs in MM, we now report, for the first time, the development of a new fully human anti-CD38 IgE as a potential targeted immunotherapy for MM. The anti-CD38 IgE is properly assembled and secreted and exhibits the correct m.w. as demonstrated by SDS-PAGE and binds antigen (CD38) and FcεRI as demonstrated by flow cytometry. We also showed that anti-CD38 IgE triggers in vitro degranulation of rat basophilic leukemia cells expressing human FcεRI (RBL SX-38) in the presence of the human MM cells expressing CD38 (MM.1S). This result is relevant since MM tumors are infiltrated by mast cells where they contribute to angiogenesis and MM growth [The success of the IgG1 antibodies daratumumab  anaphylaxis in transgenic mice expressing the human FcεRIα subunit that binds IgE ,38, trigneu (ECDHER2) bound to anti-HER2/neu IgE and anti-PSA IgE, respectively [®) [A major concern in the use of IgE as a cancer therapeutic is the possible induction of a systemic type I hypersensitivity (anaphylactic) reaction, which unfortunately, cannot be addressed in the animal models used in these studies. This is a concern since circulating soluble CD38 (sCD38) has been detected in MM patients ,61. Howeectively ,25. Althectively ,43, CD38ectively ,43,44,64ectively ,46,52,53ectively ,30,31. Mvely [®) ,66, withIn summary, our studies describe a fully human anti-CD38 IgE antibody that demonstrates IgE activity in vitro and in vivo including antitumor activity against human MM. To our knowledge, this is the first IgE to show both in vitro and in vivo efficacy against a hematological cancer, more specifically a plasma cell cancer (in an aggressive disseminated murine model) and the first to target CD38. Taken together, our results suggest that the anti-CD38 IgE antibody would be effective in humans affected with MM and potentially in other hematopoietic malignancies expressing CD38. However, further studies are necessary to assess the suitability of the anti-CD38 IgE antibody as a MM therapy. Regardless of whether or not anti-CD38 IgE becomes a MM therapeutic, the present studies support the use of IgE-based therapy targeting different antigens for the treatment of MM and potentially other hematopoietic malignancies. It is also important to point out that in cancer therapy, and especially in MM, combinatorial treatment with multiple drugs is part of the standard of care. In this light, the IgE technology is not necessarily a replacement or competitor of other therapeutic approaches, including antibodies of the IgG class, but can be used in new combination cancer therapy strategies.The following patent application has been filed: No. PCT/US2021/048714 .


In this work we examined how simulated optogenetic manipulations of inhibitory cells modifies temporal learning and recall based on these mechanisms. We show that disinhibition and excess inhibition during learning or testing cause characteristic errors in recalled timing that could be used to validate the model in vivo using either physiological or behavioral measurements.The brain uses temporal information to link discrete events into memory structures supporting recognition, prediction, and a wide variety of complex behaviors. It is still an open question how experience-dependent synaptic plasticity creates memories including temporal and ordinal information. Various models have been proposed to explain how this could work, but these are often difficult to validate in a living brain. A recent model developed to explain sequence learning in the visual cortex encodes intervals in recurrent excitatory synapses and uses a learned offset between excitation and inhibition to generate precisely timed “messenger” cells that signal the end of an instance of time. This mechanism suggests that the recall of stored temporal intervals should be particularly sensitive to the activity of inhibitory interneurons that can be easily targeted  Mammalian brains are very good at learning to recognize, generate, and predict temporal sequences. This ability is required to plan and execute precisely timed movement sequences, recognize temporal patterns, turn patterns of sounds into words and words into sentences, and is at the root of most complex behaviors. Neuroscience has described neural mechanisms capable of performing this task in specific brain areas, e.g., bird song generation  or eyeliin vivo, but it is not known how localized plasticity rules shape circuits to store or access temporal information. One idea is that cholinergic signaling modulates Hebbian-type plasticity to create recurrent excitatory feedback with decay dynamics matching temporal information contained in visual stimulus patterns  introduces random noise into the leak current using a scaled normal distribution, xg and xE represent the conductance and reversal potential for a Leak (L), Excitatory (E), and Inhibitory (I) currents, and Iopto is a simulated optogenetic current. Neurons spike when iV reaches threshold and are held at −61 mV for a 2 ms refractory period.where C is the membrane capacitance, i is the product of the synaptic weight  between two neurons and an activation variable, is, that increases by a percent ρ following presynaptic spikes  is an indicator function equal to 1 when the simulated laser is active and 0 otherwise and gopsin sets the strength and valence  of optogenetic activation. The σr(t) term introduces noise drawn from a scaled standard normal distribution and scales the efficiency term Neff. Different values of gopsin were used to create inhibitory or excitatory currents in different experiments. This simplified model was motivated by previous works simulating optogenetic currents based on biophysics and light flux  scaled by a learning rate parameter (ηx), saturate at a maximum value (x).where Wij) by a reinforcement or reward signal (R(t)) scaled by a learning rate parameter (η):During learning, eligibility traces are converted into synaptic weights  marked to show quartiles and the total data range. All violin plots in a single panel were plotted using the same kernel estimation bandwidth. The statistical effect of optogenetic manipulations during and training and testing was determined using a 2-Way ANOVA test in SPSS.The Cone and Shouval model  represenIopto. This current was included in the inhibitory population, could be turned on and off at specific timepoints during a network simulation, and could be made to have either an inhibitory or excitatory effect by varying the gopsin parameter . To determine the effect manipulating the inhibitory cells would have on a previously trained temporal interval, we first trained a column to represent a single interval of 750 ms and ran the network over multiple independent trials while activating a simulated laser to perturb activity in the Inhibitory cells. By manipulating the gopsin parameter, we were able to simulate the effects of both excitatory and inhibitory manipulation of the I cells on temporal reports, quantified as the time of peak firing in the M cells. As shown in To test this, we modified the neuron model used by Cone and Shouval to include a simulated optogenetically controlled current, gopsin. It quickly because apparent that there was a limited functional range over which these manipulations produced reasonable results. Too much Excess Inhibition quashes activity in the T and M populations, and too much Disinhibition causes an explosion of activity reminiscent of epilepsy. By algorithmically quantifying these two outcomes, we were able to identify a function range of gopsin where the network responded to external stimulation with interpretable results , we reasoned that manipulation of I cells during training would similarly lead to specific predictions about how the network should behave in the presence of post-training manipulations during recall trials. Specifically, we hypothesized that recurrent excitatory weights would increase or decrease in final magnitude to compensate for up or down-regulation of inhibitory activity during training.To test this, we modified our training procedure to include constant stimulation of either excitatory or inhibitory opsins in I cells during training , top. Inin vivo during temporal learning trials.To understand why manipulating inhibitory cells during training has this effect on reported time, we plotted the distribution of recurrent excitatory synaptic weights within the T population. A representative example in The concept of “time” is notoriously difficult to pin down, so perhaps it’s not surprising that we don’t have a good handle on the neurobiological basis of temporal perception. Despite a good deal of interest in the subject, there are still many more questions than answers about how time is represented in the brain. Even less is known about how activity dependent plasticity shapes cortical circuits to create memories that include temporal information, or how the brain uses this stored information to predict how events will unfold in time. One of the reasons for this is that we haven’t identified many neural correlates of learned time that can be easily measured and linked to either physiological activity or behavioral outcomes. A variety of models have been developed to account for temporal perception, but often at a level of abstraction that makes it difficult to tie back to specific biology.The visual system, including primary cortical areas, has emerged over the last decade as an unexpectedly rich system to study time, sequence learning, and temporal predictions. Starting with the demonstration that cells in rat V1 can learn evoked dynamics that predict when a reward will be delivered following visual stimulation , visual In this paper we show that a unique aspect of this model’s timing mechanism presents a viable target for experimental validation. Our inclusion of a simulated optogenetic current in the membrane voltage equation of inhibitory cells in a simulated network demonstrates that excess inhibition tends to lengthen the duration of temporal reports in trained networks and disinhibition tends to shorten them. We also show that a network trained with either excess inhibition or disinhibition will recall incorrect times, underestimating and overestimating, respectively. The implication is that optogenetic stimulation targeting inhibitory interneurons can be used validate the model by artificially slowing down or speeding up learned internal clocks. Put another way, if an animal learns to represent a specific temporal profile using the mechanisms proposed by Cone and Shouval, optogenetic excitation of inhibitory neurons participating in the representation should cause the animal’s internal clock representing the time to run slow. Optogenetic silencing of the inhibitory neurons should cause the clock to run fast. Any physiology or behavior dependent on the temporal representation should similarly shift and the same approach would be valid whether the coding occurs in V1 or some other cortical region.We targeted inhibitory neurons because of our analysis suggested an important role in producing organized readouts of stored intervals, but there are additional reasons to focus on them as well. As a practical matter, there are a variety of tools that can be used to manipulate inhibitory activity. The literature is full of examples showing how the Cre-LoxP system  can be uin vivo would produce statistically significant outcomes, we do not think that these statistics are necessary to convincingly link the overall trends to specific elements of the network timing structure. Because the precise statistics depend entirely on the parameters used for a particular run, these numbers have little predictive power when making experimental design decisions in vivo. This is particularly true because we chose to use a simplified model of optogenetic current rather than more biophysically realistic alternatives . While a more realistic optogenetic model could, in principle, provide more guidance for designing experiments based on this work we do not think this possibility is worth the additional complexity since many of the relevant parameters are difficult to either estimate or control in vivo  and since the many parameters in the Cone and Shouval model itself are rough approximations.We used a standard ANOVA to show that different levels of optogenetic manipulation during training and testing result in statistically different temporal reports in our simulated networks. While this is useful to demonstrate that the effect size of these manipulations is large enough to expect similar experiments This work does not address how other timing models would respond to similar manipulations of inhibitory cells. While there are compelling reasons to think that the plasticity responsible for learning temporal representations occur in local cortical circuits , it is possible that learning requires timing mechanisms outside of the cortex. It was recently shown, for example, that hippocampal lesions can prevent sequence representations from forming in the primary visual cortex  and placin vivo should slow down or speed up recalled temporal memories in predictable ways. This is true whether manipulations occur after specific timing has already been learned or during training. While further refinements of the model would allow more precise predictions, these results are sufficient to motivate and guide future experiments testing whether the brain uses an offset between decaying excitatory and inhibitory activity to signal time in the cortex.The main takeaways from this work are that trained temporal reports in the Cone and Shouval model are particularly sensitive to lateral inhibition, and that optogenetic manipulation of inhibitory cells The original contributions presented in this study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.JR and JG: conception and experimental design, data analysis, visualization, and writing the manuscript. JR: coding. Both authors contributed to the article and approved the submitted version.


This study employs time-frequency domain approach to investigate the spillover effects of renminbi (RMB) exchange rate among the Regional Comprehensive Economic Partnership (RCEP) member countries. Utilizing daily data spanning from August 2010 to August 2022, we find that currencies in the RCEP region demonstrate significant interaction, which is primarily driven by short-term spillover, and ascend in response to major economic and political events. With respect to the influence of RMB, it displays frequency bands heterogeneity. Specifically, RMB tends to be a net receiver in the short term, but it primarily functions as a net transmitter in the long term. Notably, our analysis of time-varying spillover effects indicates that both domestic exchange rate regime reforms and external political and economic shocks amplify the net spillover effects of the RMB, which may be reflected in short-term connectedness or captured by long-term connectedness. On 15 November 2020, the Regional Comprehensive Economic Partnership (RCEP) was officially signed by 15 member countries, including ASEAN 10, China, Japan, South Korea, Australia, and New Zealand. As the largest trading bloc in the world, RCEP member countries collectively represent approximately 30% of the global population, GDP, and trade volume [In global and regional development, economic integration often goes hand in hand with financial integration . The forThe transmission of exchange rate fluctuations stems from broad economic and financial linkages, primarily through three key channels: trade, finance, and sentiment , 7–12. FThe literature on exchange rate markets connectedness is quite extensive, encompassing the interlinkages among currencies of developed countries –26, spilOur research closely aligns with the following two strands of literature. The first is based on the external currency model proposed by Frankel and Wei in 1994 , which eWe utilized time-frequency domain approach to investigate the spillover effects of RMB exchange rate among RCEP member countries. This study provides following potential marginal contributions: (i) enriching the research on the regional impact of RMB. Previous studies on RMB spillover effects have mainly focused on ASEAN and Belt and Road countries. To our knowledge, there has been no research on the spillover effects of RMB in the RCEP region. RCEP holds significant importance in promoting economic integration in the Asia-Pacific region during the COVID-19 pandemic , and theThe findings of the study demonstrate that there exist significant interrelationships between currencies in the RCEP region, primarily driven by short-term spillover effects that increase during significant economic and political events. Regarding the spillover effects of the RMB, it primarily plays the role of a net receiver in the short term, while mainly acting as a net transmitter in the long term. This suggests that the influence of RMB is primarily achieved through long-term channels such as international trade and foreign direct investment. From a time-varying perspective, both domestic exchange rate regime reforms and external political and economic shocks increase the net spillover effect of the RMB, which may be reflected in short-term connectedness or captured by long-term connectedness. Consistent with the research of Zhou et al. , the infThe remainder of this paper is structured as follows: Section 2 presents the research methodology and statistical analysis of the data. In Section 3, the empirical results are discussed. Finally, Section 4 provides the conclusion and implications of this study.In this paper, the dynamic spillover index method proposed by Chatziantoniou et al. is carrixt and ϵt are the N-dimensional column vectors, representing the exchange rate variable and error vector, Σt stands for a time-varying variance-covariance matrix (N×N), and Φit, i = 1,…,p is also time-varying, denoting an N×N coefficient matrix.We begin by building a TVP-VAR model as follows:∞) process.Lp is identity matrix.If the above TVP-VAR variance-covariance process is stationary, then it can be simplified into the following TVP-VMA  The total directional spillover index to others (TO) measures the total spillover from variable i to all other variables:We can then compute all of the spillover indices, beginning with the total spillover index (TSI). Here is the expression:i:(ii) The total directional spillover index from others (FROM) measures the total spillover from all other variables to variable (iii) The net total directional spillover index (NET) equals the total directional spillover index to others (To) minus the total directional spillover index from others (From), i.e.,NETit(H)>0, variable i is a net transmitter in the whole system and vice versa.Cijt(H)>0, variable j has more influence over variable i than variable i has over variable j, and vice versa.In addition, we sometimes need to measure the connectedness between two variables, which can be defined asxt at frequency ω can be expressed as:To further explore the spillover effect at different frequency bands, we first define the frequency response function, As in the time domain, we prefer frequency GFEVD as follows,θijt(ω) denotes the contribution of jth variable to the portion of the spectrum of ith variable at the frequency ω. After normalizing it, the expression is as follows:Where d = : a, b∈, a<b, the frequency GFEVD at frequency band d can then be expressed asΓi(ω) stands for the weighting function. Based on the above study, we can calculate accurately the various spillover indices at the frequency band d:Typically, we are interested in spillover effects within a particular band of frequencies, rather than at any particular frequency. Thus, given a random frequency band: This article aims to analyze the time-frequency spillover effects of RMB exchange rate among RCEP countries. With the exception of currencies pegged to either the US dollar or Singapore dollar as well as those with a large amount of missing data , we employ a daily exchange rate dataset (against the US dollar) consisting of RMB and currencies of other ten RCEP members, namely the onshore RMB (CNY), the offshore RMB (CNH), the Japanese yen (JPY), the South Korea won (KRW), the Australian dollar (AUD), the New Zealand dollar (NZD), the Thailand baht (THB), the Singapore dollar (SGD), the Indonesian rupiah (IDR), the Philippines peso (PHP), the Malaysian ringgit (MYR) and the Vietnam Dong (VND). The sample period runs from 23 August 2010 to 19 August 2022, which is comprehensive and can present the RCEP development pathway since it was proposed in 2012. The starting point of the sample period is determined by the availability of CNH. All the data series are obtained from Bloomberg.We compute the returns using the logarithmic difference on the raw exchange rate data, with negative (positive) returns reflecting the appreciation (depreciation) of the home currency. p) for the generalized vector autoregression model is selected by the Akaike information criterion (AIC) and the Schwartz criterion (SC). Furthermore, in this paper, we decompose the spillover indices into two different frequency bands, namely d1 = , d2 = . We define them as high frequency (1–5 days) and low-frequency (more than 5 days), representing the short-term and long-term spillover effects respectively. According to the study of Barunik and Krehik [H) requires sufficiently large, otherwise the methodology will not work. Thus, referring to some recent studies [H) to 100 days.In this section, we estimate the spillover effects in both the time and frequency domains. The optimal lag length , followed by AUD (24.94%) and NZD (17.11%). This is in line with the findings of Bouri et al. and AnweWe focus our attention on CNY. As shown in 3.1.2 Static spillover effects between CNH and currencies of RCEP members. To arrive at a more comprehensive analysis of the connectedness between RMB and currencies of RCEP members, we quantify the spillover effects of CNH based on the time-frequency domain approach, with the results shown in Tables Similar to the results of CNY, it is apparent from Upon analyzing the net total directional spillovers, it is evident that SGD, AUD, and NZD remain the primary net transmitters, with values of 42.91%, 27.21%, and 18.48%, respectively. These values exceed those of the CNY network, indicating that other currencies, such as KRW, MYR, and PHP, receive more significant net spillovers. However, the inverse holds for CNH.As indicated in The aforementioned findings indicate that CNH may wield a greater influence than CNY, aligning with the findings of Zhou et al.  and ChowIn the study above, our objective was to ascertain the mean spillover effect between RMB and currencies of RCEP members. However, the RMB exchange rate regime reform implemented on 11 August 2015 ("8.11" RMB exchange rate regime reform), has significantly influenced both CNY and CNH . As a reBased on Tables Previous studies have highlighted that market turmoil triggered by significant economic and political events can affect the transmission of spillovers across foreign exchange markets . As suchWe employ the TVP-VAR model to investigate the dynamic spillover effects between RMB  and currencies of RCEP members, encompassing both the time and frequency domains.The outcomes of the correlational examination are presented in We begin our analysis with the time-varying total spillover effect, which reflects the dynamic connectedness among currency markets over the entire sample period. As depicted in To), total directional spillover from other currencies to CNY (CNYFrom), and net total directional spillover of CNY (CNYNet), respectively. It is important to note that CNYNet represents the difference between CNYTo and CNYFrom, indicating that CNY is a net transmitter(receiver) when CNYNet is positive(negative).Next, we focus on the role of CNY in the whole currency market. The relevant findings are illustrated in To and CNYFrom are highly event-dependent and vary over time. Notably, the "8.11" RMB exchange rate regime reform boosted CNYTo sharply, particularly in the short term. Zhou et al. arrived at the similar conclusion in their study on the influence of the Renminbi in countries along the Belt and Road [To is more sensitive to events than CNYFrom. For instance, the "8.11" RMB exchange rate regime reform, the China-US trade war, and the COVID-19 pandemic have had a more significant impact on CNYTo than on CNYFrom. Due to the absence of a freely floating exchange rate regime and a fully open capital account, CNY is less vulnerable to shocks from other currencies. This implies that the CNY has a greater impact on other currencies during significant event shocks, while also possessing the capability to withstand the repercussions of shocks to other currencies.Similar to the total spillover, CNYand Road . It is wNet, the time-varying results depicted in Regarding CNYIn conclusion, we posit that the net transmission position of CNY has undergone significant improvement post the "8.11" RMB exchange rate regime reform, shifting from a pure net receiver to an alternating net receiver and net transmitter. Moreover, the influence of CNY is sensitivity to major events. Certain events may amplify the short-term impact of CNY, while others may contribute to long-term influence.As can be seen from To), total directional spillover from other currencies to CNH (CNHFrom), and net total directional spillover of CNH (CNHNet), respectively. It should also be noted that CNHNet equals to CNHTo minus CNHFrom. When it is positive (negative), CNH acts as a net transmitter(receiver).We now turn to the spillover effect of CNH. To and CNYTo exhibit similar patterns, both oscillating upwards and being more prevalent in the short term. Nonetheless, before August 2015, CNHTo exerted a stronger influence than the CNYTo, indicating the greater market influence of the CNH. While the “8.11” RMB exchange rate regime reform has improved both CNHTo and CNYTo, the latter experienced a greater increase. In specifics, CNYTo at the end of August was approximately five times higher than at the beginning of August, while CNHTo only doubled. More interestingly, COVID-19 and the China-US trade war also had a greater impact on the growth rate of CNYTo.Firstly, as displayed in From was higher than CNYFrom due to more price elastic of CNH. Throughout the entire sample period, consistent with CNY, CNHFrom is less affected by events than CNHTo, which demonstrates that CNH has a high capacity to resist market risk.Secondly, from 2014 to August 2015, CNHNet illustrated in Net, CNHNet was negative on all frequency bands until the “8.11” RMB exchange rate regime reform, meaning that CNH assumed a considerable role as a net receiver. The “8.11” RMB exchange rate regime reform also caused a short peak in the CNHNet, which subsequently returned to net receiver status until the end of 2017. Since then, CNH has switched between being a net receiver and a net transmitter, with the duration of the net transmitter being longer than that of CNY. Specifically, we note that CNH remains a net transmitter from the end of 2017 to the end of March 2020 and again from February 2021 to August 2022 (excluding some short periods). Long-term connectedness dominated in both of the above intervals, except for early 2020. As already mentioned, the first interval was marked by the China-US trade war and the COVID-19 pandemic, while the second interval was characterized by the promotion of vaccines in China.Finally, let us proceed to the dynamic evolution of CNHIn brief, following the "8.11" RMB exchange rate regime reform, the CNH emerged as a net transmitter, particularly over the long term. The net transmitter status of the CNH has been bolstered by events such as the COVID-19 pandemic and the China-US trade war. Notably, CNH wields greater influence than the CNY. However, in times of significant market turbulence, compared to CNH, the directional spillover of CNY to the currencies of RCEP members exhibits a more significant ascent. The reason for this could be attributed to the relatively shallow liquidity base that constrains the offshore RMB market [In this section, we conduct the several research tests to ensure the robustness of our empirical results.Firstly, we validate the static spillover effects using the average results of the TVP-VAR model, as shown in Tables p) and forecasting horizon (H) [p) to 3 and keep the forecasting horizon (H) at 100, while in Figs H) to 85 and retain the lag length (p) at 1. Compared to the results in section 3.2, there are no significant changes in the dynamic spillover effects. Judging from the dynamic evolution of the total spillover, it is sensitive to international economic and political events and shows an upward trend during the sample period. From the perspective of the dynamic spillovers of RMB, the “8.11” RMB exchange rate regime reform, the China-US trade war, and the COVID-19 pandemic all increased the net total directional spillover of RMB. However, it is evident that the evolution of the net total directional spillover of CNH and CNY is different in detail. Following the “8.11” RMB exchange rate regime reform, CNH has been playing the role of a net transmitter in the long term, while CNY has alternated between a net transmitter and a net receiver. Thus, our findings in Figs p) and forecasting horizons (H). The slight change is only shown by the fact that the spillover effect fluctuates a little more sharply when the lag is longer.Secondly, considering that the spillover may be sensitive to the lag length (izon (H) , 8, we cIn summary, the results in this section using different empirical methods remain largely consistent with the empirical findings in the main text and can demonstrate the good robustness of the main conclusions of this paper.The correlation between economic integration and financial integration in global and regional development has consistently been demonstrated . TherefoFirstly, the currencies in the RCEP region display a strong interaction, as demonstrated by the total spillover indices, which range from 40% to 75%. The interactions exhibit heightened sensitivity to global economic fundamentals, which results in an increase of spillover effects during significant events. In terms of frequency bands, the total spillover effect is more susceptible to short-term factors, indicating that the market processes information promptly and efficiently.Secondly, the spillover effect of the RMB shows heterogeneity across various frequency bands and countries. In terms of frequency bands, RMB tends to be a net receiver in the short term, but it primarily functions as a net transmitter in the long term, implying that the influence of RMB is mainly driven by long-term factors, such as international trade and foreign direct investment. Concerning countries, the primary net receivers of information from RMB are JPY and VND, while SGD and AUD primarily transmit net spillover to RMB.Moreover, both domestic exchange rate regime reforms and external political and economic shocks increase the net spillover effect of the RMB, which may be reflected in short-term connectedness or captured by long-term connectedness. Following the "8.11" RMB exchange rate regime reform, the RMB changed from being a complete net receiver to an alternating status of being a net receiver and a net transmitter. The China-US trade war has heightened the long-term impact of RMB, while the COVID-19 pandemic contributes to short-term influence.Finally, the net spillover effect of CNH consistently surpasses that of CNY, indicating that CNH wields greater influence than CNY. Nevertheless, in times of significant market turbulence, the directional spillover of CNY to the currencies of RCEP members exhibits a more significant ascent. With the opening of China’s capital account and the development of the onshore RMB market, the influence of CNH may gradually diminish.The above findings have important implications for both policymakers and market participants. On the one hand, market regulators should pay due attention to risk contagion in the foreign exchange market, especially during the outbreak of international political and economic events, strengthen risk prevention, and further promote cooperation among member countries under the RCEP framework. On the other hand, for investors, it is necessary to focus on preventing the input risks arising from the occurrence of risk events and identify the frequency bands of risk contagion to achieve investment risk management. In addition, our research shows that the RMB mainly assumes the role of a net transmitter in the long-term, while it is mostly a net receiver in the short-term. Therefore, we should continue to deepen the market-oriented reform of the RMB exchange rate and further increase the exchange rate’s flexibility to enhance the net transmission capacity of RMB in the short term.There are several limitations in this study. Firstly, due to the unavailability of data, the Lao kip and Myanmar Kyat were not included in our analysis. In the future, if more relevant data becomes available, we aim to construct a more comprehensive spillover network. Secondly, this paper solely focused on examining the spillover effect of the RMB exchange rate among RCEP member countries and did not provide an econometric analysis of the factors that may affect the spillover. Future research could investigate these factors, potentially leading to new insights.S1 File(XLSX)Click here for additional data file.


Prevailing methods to measure wasting rely on cross-sectional surveys that cannot measure onset, recovery and persistence—key features that inform preventive interventions and estimates of disease burden. Here we analyse 21 longitudinal cohorts and show that wasting is a highly dynamic process of onset and recovery, with incidence peaking between birth and 3 months. Many more children experience an episode of wasting at some point during their first 24 months than prevalent cases at a single point in time suggest. For example, at the age of 24 months, 5.6% of children were wasted, but by the same age (24 months), 29.2% of children had experienced at least one wasting episode and 10.0% had experienced two or more episodes. Children who were wasted before the age of 6 months had a faster recovery and shorter episodes than did children who were wasted at older ages; however, early wasting increased the risk of later growth faltering, including concurrent wasting and stunting (low length-for-age z-score), and thus increased the risk of mortality. In diverse populations with high seasonal rainfall, the population average weight-for-length z-score varied substantially (more than 0.5 z in some cohorts), with the lowest mean z-scores occurring during the rainiest months; this indicates that seasonally targeted interventions could be considered. Our results show the importance of establishing interventions to prevent wasting from birth to the age of 6 months, probably through improved maternal nutrition, to complement current programmes that focus on children aged 6–59 months.Sustainable Development Goal 2.2—to end malnutrition by 2030—includes the elimination of child wasting, defined as a weight-for-length  An analysis of longitudinal cohort data across diverse populations suggests that the incidence of wasting between birth and 24 months is higher than previously thought, and highlights the role of seasonal factors that affect child growth. Children are considered wasted if their weight-for-length z-score (WLZ) is more than two standard deviations below the median of international standards, and severe wasting is defined as three standard deviations below the median3. Wasted children have weakened immune systems4, predisposing them to infections and more severe illness once infected5. Wasting in very young children increases their risk of mortality (relative risk: 2.3), and this risk increases further if they are also stunted and underweight (defined as a length-for-age z-score (LAZ) below –2 and a weight-for-age z-score (WAZ) below –2, respectively; relative risk: 12.3; ref. 6). Longitudinal studies have shown that wasting is also associated with a higher risk of stunting7 and poor neurocognitive development at older ages9. Community-based identification and management of severely wasted children (WLZ below –3), including treatment with high-calorie, ready-to-use-therapeutic foods, has proven effective10, but rates of relapse and mortality remain high in this fragile subgroup12. Primary prevention of wasting would be preferable to treatment, but there are few proven preventive interventions, especially in infants under 6 months. Nutritional intervention trials have had mixed success, with no evidence for reductions in wasting with breastfeeding support from birth, but with larger reductions achieved by administering small-quantity lipid-based nutrient supplements between the ages of 6 months and 24 months 14.Wasting is a form of undernutrition that results from a loss of muscle and fat tissue from acute malnutrition. It affects an estimated 45 million children under the age of 5 years (6.8%) worldwide, with more than half of these children living in South Asia16. However, a more complete understanding of the epidemiology of wasting and how it varies by age is key to developing and targeting preventive interventions18. Unlike the cumulative process of linear growth faltering and stunting19, wasting varies considerably over time, both within individuals and within populations21. The dynamic nature of wasting means that the number of distinct episodes a child experiences might be poorly captured in cross-sectional, survey-based estimates22. Furthermore, seasonal patterns of wasting onset in relation to changes in food insecurity or disease can only be measured accurately with longitudinal data24. A synthesis of longitudinal cohort data across diverse populations provides a unique opportunity to study the timing, dynamics and burden of wasting in infants and young children, and to fill key knowledge gaps to inform future prevention efforts.Wasting is thought to occur mainly from 6–24 months—the crucial period in which exclusive breastfeeding is no longer recommended, and adequate, appropriate and safe complementary feeding is requiredHere we report a pooled analysis of 21 longitudinal cohorts from 10 low- or middle-income countries (LMICs) in South Asia, sub-Saharan Africa and Latin America, in which length and weight were measured monthly in children of 0–24 months. Our primary objectives were to produce large-scale estimates of wasting incidence and recovery and to quantify the temporal and regional variation. We also assessed the concurrence of wasting and stunting and compared estimates of wasting prevalence and incidence. We analysed data from the Bill & Melinda Gates Foundation’s Knowledge Integration (Ki) database, which has aggregated studies on child growth and development. Inclusion criteria were defined to select cohorts that are representative of general populations in LMICs, with sufficiently frequent measurements to investigate the acute, dynamic nature of wasting. Cohorts were included if they: (1) were conducted in LMICs; (2) enrolled children between birth and the age of 24 months and measured their length and weight repeatedly over time; (3) did not restrict enrolment to acutely ill children; (4) had a median birth year of 1990 or later; and (5) measured anthropometry at least monthly  of WLZ (z-scores of greater than 5 or less than –5), 212 (0.1%) measurements of LAZ (z-scores of greater than 6 or less than –6) and 216 measurements (0.1%) of WAZ (z-scores of greater than 5 or less than –6), following WHO recommendations26. Most included cohorts did not measure children after the age of 24 months, so analyses focused on birth to 24 months. Cohorts ranged in size from 160 children in the Transmission Dynamics of Crypto (TDC) cohort to 2,931 children in the MRC Keneba cohort  2006 growth standardsz-score measurements to population-based samples in demographic and health surveys (DHSs). Mean z-scores in Ki cohorts were generally representative on the basis of country-level DHS estimates, with lower WLZs  in Guatemala, Pakistan and South Africa and higher WLZs in Brazil and Guatemala , implicating causes of poor fetal growth such as maternal malnutrition, maternal morbidities and maternal small stature as key regional drivers of wasting32. Severe wasting followed a similar pattern but was much rarer  versus 35 days ). Incident wasting during the rainy season increased a child’s risk of experiencing another wasting episode in the following dry season , and children who were wasted during the rainy season during their first year of life were 1.9 times  more likely to be wasted during the next rainy season.z  depending on the month the child was born  were persistently wasted. Children in South Asia had the highest proportion of measurements with wasting . Almost half of children who had prevalent growth faltering met two or more of these three growth faltering conditions, with 17–22% of all children experiencing multiple conditions after the age of 12 months  than was previously known. Children in all included cohorts experienced a higher incidence compared with prevalence, owing to the episodic nature of acute malnutrition; this pattern was most stark in South Asian cohorts, in which, from birth to 24 months and pooled across cohorts, 52.2% of children experienced at least one wasting episode, 7.3% were persistently wasted and 10.1% had experienced concurrent wasting and stunting. This evidence shows that the cumulative, child-level burden of wasting is higher than cross-sectional measures of prevalence would suggest, and that assessments of wasting and stunting in isolation do not account for their joint burden, which can be substantial. This is of particular relevance in South Asia, where the largest number of stunted and wasted children live, and where, although the prevalence of stunting is decreasing, the prevalence of wasting is not46.Nearly all large-scale studies of child wasting (including the DHS programme) report the point prevalence of wasting, which has enabled broad comparisons between populations but does not capture the number of episodes of wasting during the course of childhood50. To our knowledge, our finding that the wasting incidence was highest from birth to the age of 3 months has not been previously reported across diverse cohorts. We found higher rates of recovery among children who were wasted before 6 months, but early wasting episodes predisposed children to subsequent episodes at older ages, which tended to be longer and more likely to co-occur with stunting. These new findings suggest that the prenatal period through to 6 months old should be a focus for preventive wasting interventions, because preventing episodes during this early window would reduce the risk of later, more severe forms of growth faltering and lower a child’s risk of all-cause mortality substantially, as we detail in a companion paper32.Our results show consistent patterns in the timing of wasting onset by age and by season, with implications for therapeutic and preventive interventions. Wasting incidence was highest from birth to the age of 3 months, and among children who experienced any wasting during their first 24 months, 48% had their first episode by 3 months. Children born wasted were much more likely to experience more growth faltering at older ages, including more severe forms such as persistent wasting from 6 to 24 months and concurrent wasting and stunting at 18 months Fig. . The agez at birth, with consequences that persisted throughout the first 24 months , so using WLZ underestimates wasting at birth58.We included all longitudinal observational studies and randomized trials available through the Ki project on April 2018 that met five inclusion criteria  below the 2006 WHO standard –2 WLZ. Similarly, prevalent severe wasting was defined as the proportion of measurements below the 2006 WHO standard –3 WLZ. For each age, we included children with WLZ measurements within one month before and after that age in the point-prevalence estimate .z in the prior measurement to below –2 z in the current measurement. Similarly, we defined severe wasting episodes using a cut-off of –3 z. We assumed a 60-day washout period between episodes of wasting before a new episode of wasting could occur  as the proportion of children not wasted at the start of the period who became wasted during the age period (the proportion of children who had the onset of new episodes during the period). This differs from period prevalence, which would include any children who had any measurement of WLZ < –2 during the period (including children who began the period wasted). Period prevalence would thus also include, in the numerator and denominator, children who were wasted at the start of the period, whereas incidence proportion excludes them.z among children who are currently wasted or severely wasted. We required a child to maintain a WLZ above –2 for 60 days to be considered ‘recovered’. Children were only considered ‘at risk’ for recovery if their prior measurement was below –2 z. We measured the proportion of children who recovered from moderate wasting (WLZ < –2) within 30, 60 and 90 days of the onset of the episode. We assumed that recovery from wasting was spontaneous because we did not have consistent information on referral guidelines across cohorts in the analysis, but some children with moderate wasting might have been referred to clinical facilities for outpatient treatment. Wasting recovery might thus be higher in these highly monitored cohorts than in the general population owing to treatment referrals.Recovery from wasting was defined as a change in WLZ from below to above –2 Wasting duration was estimated by counting the days between the onset of wasting and recovery within an individual child. We assumed that the episode started or ended at the midpoint between measurements. For example, if a child was not wasted at age 40 days, wasted at age 70 days and not wasted at age 100 days, the duration of the wasting episode was: (70 − 40)/2 + (100 − 70)/2 = 30 days. We calculated the median duration of wasting episodes among cohorts in which children recovered during the study period from more than 50% of observed wasting episodes, as the duration of episodes that extended beyond the study period is unknown. Therefore, the median duration could only be calculated when less than half of episodes were censored.The incidence rate of wasting was calculated during defined age ranges as the number of incident episodes of wasting per 1,000 child-days at risk during the age range. Children were considered ‘at risk’ for incident wasting episodes if they were not currently wasted and were classified as recovered from any previous wasting episode (beyond the 60-day washout period). Therefore, wasted children, or children within the washout period, did not contribute to the person-time at risk for wasting used to calculate wasting incidence. To calculate the person-time at risk of wasting, we assumed that the onset of a wasting episode occurred when the child’s age was at the midpoint between the measurement of WLZ ≥ –2 and the measurement of WLZ < –2, and conversely the time of recovery occurred when the child’s age was at the midpoint between the last measurement of WLZ < –2 and the first measurement of WLZ ≥ –2 within the 60-day washout period Fig. .40.Persistent wasting was defined as a greater than 50% longitudinal prevalence of below –2 WLZ (wasting), and analogously a greater than 50% longitudinal prevalence of below –3 WLZ for persistent severe wastingConcurrent prevalence of wasting and stunting was defined as the proportion of measurements at a specific age when a child was both wasted and stunted at the same measurement. For each age, we included children with WLZ and LAZ measurements within one month before and after that age in the point-prevalence estimate .Prevalent underweight was defined as the proportion of measurements at a specific age below the 2006 WHO standard –2 WAZ. For each age, we included children with WAZ measurements within one month before and after that age in the point-prevalence estimate .https://hdr.undp.org/); the percentage of the country living on less than US$1.90 per day; and under-5 mortality rates . Within each country, in years without available data, we linearly interpolated values from the nearest years with available data and extrapolated values within five years of available data using linear regression models based on all available years of data.We stratified the above outcomes of interest within the following subgroups: child age ; region of the world ; month of the year; and the combinations of the above categories. We also pooled wasting-incidence proportion by categories of three country-level characteristics: the percentage of gross domestic product devoted to healthcare goods and spending 59. Median durations were pooled across cohorts using the unweighted median of medians method60.We conducted a two-stage individual participant meta-analysis, estimating wasting outcomes within specific cohorts and pooling estimates within each age stratum using random-effects models. For example, we estimated each age-specific mean using a two-step process. We first estimated the mean in each cohort, and then pooled age-specific means across cohorts allowing for a cohort-level random effect. We estimated overall pooled effects, and pooled estimates specific to South Asian, African or Latin American cohorts, depending on the analysis. We repeated the pooling of all statistics presented in the figures using fixed-effects models as a sensitivity analysis .65. Cohorts from years with a seasonal index greater than or equal to 0.9 were classified as occurring in locations with high seasonality; cohorts with a seasonal index less than 0.9 and greater than or equal to 0.7 were classified as occurring in locations with medium seasonality; and cohorts with a seasonal index less than 0.7 were classified as occurring in locations with low seasonality.R = total annual precipitation and Xn = monthly precipitation.Estimates were unadjusted for other covariates because we assumed that seasonal effects on WLZ were exogenous and could not be confounded. Mean differences in WLZ were pooled across cohorts using random-effects models, with cohorts grouped by the Walsh and Lawler seasonality indexhttps://dhsprogram.com/). We used the most recent standard DHS datasets for the individual women’s, household and length and weight datasets from each country, and we estimated age-stratified mean LAZ, WAZ and WLZ from ages 0 to 24 months within each DHS survey, accounting for the complex survey design and sampling weights. See a companion paper for further details on the DHS data cleaning and analysis19. We compared DHS estimates with mean LAZ, WAZ and WLZ by age in the Ki study cohorts with penalized cubic splines with bandwidths chosen using generalized cross-validation63. We did not seasonally adjust DHS measurements.We downloaded standard DHS individual recode files for each country from the DHS program website . We calculated the cohort-specific RTM effect and plotted the mean z-scores expected from RTM 3 months later among children who were wasted at each age in months from birth to 21 months. We used the cohort means as the population mean z-scores, and compared the expected mean WLZ with the observed mean WLZ68  initiative. Datasets are owned by the original investigators that collected the data. Members of the Ki Child Growth Consortium were nominated by each study’s leadership team to be representative of the country and study teams that originally collected the data. Consortium members reviewed their cohort’s data within the Ki database to ensure external and internal consistency of cohort-level estimates. Consortium members provided input on the statistical analysis plan, interpretation of results and manuscript writing. Per the request of consortium members, the manuscript includes cohort-level and regional results to maximize the utility of the study findings for local investigators and public health agencies. Analysis code has been published with the manuscript to promote transparency and extensions of our research by local and global investigators.Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-06480-z.Supplementary InformationThis file contains Supplementary Notes 1–8.Reporting SummaryPeer Review File


Water retention in earthen fishponds throughout a fish farming cycle is challenging due to climate-induced water loss via evapotranspiration, seepages, and lowering of the groundwater table. These processes depend on the soil hydrostratigraphic condition and constitute a major challenge for fish farmers in the Niger-Delta region of Nigeria, where seasonal variations cause groundwater levels to fluctuate. This study assesses the use of non-invasive geophysical methods, including electrical resistivity and induced polarization, to guide the selection of sites with appropriate hydrostratigraphic conditions for establishing earthen fishponds. We combined measurements of electrical resistivity and chargeability distributions to assess the subsurface of two earthen fishpond sites at Ugono-Abraka and Agbarha-Otor areas in the Niger-Delta region of Nigeria. Electrical soundings were acquired at ten locations, while two-dimensional electrical resistivity and Induced polarization were acquired across five transects using Schlumberger and dipole-dipole electrode configurations. The field data were inverted using IP2win, and Diprowin software. The geophysical models were combined with lithological data from soil cores to characterize the subsurface stratigraphy, while measured clay contents were used to estimate infiltration coefficients relying on established petrophysical relationships. The delineated subsurface properties at Ugono-Abraka and Agbarha-Otor show higher variations than assumed by practitioners. The complementary results of low resistivity (20–140 Ωm) and high chargeability (10–50 msec) revealed areas with clay-rich sediments. Soil samples confirmed higher clay contents of up to 10% at Ugono-Abraka and low values of 2% at Agbarha-Otor. Estimated infiltration coefficients are lower at the Ugono-Abraka site (1.6 m/day) compared to Agbarha-Otor (8.4 m/day). This implies variable water loss in the earthen fishponds; hence, we recommend characterizing these variations using non-invasive geophysical methods before establishing medium to large-scale earthen fishponds in the area. The easThe establishment of fish farms within the Niger-Delta region of Nigeria using earthen fishponds involves digging a selected area to establish a depression that extends through the shallow water table, typically between <1 and 3 m deep, depending on the location see  19]. Th. Th19]. in situ hydrogeological testing, significantly improves understanding of the subsurface stratigraphic heterogeneity and estimation of its hydraulic properties such as infiltration coefficient or hydraulic conductivity [Understanding the subsurface conditions, including the hydraulic properties of fishpond sites, mostly in tropical areas, has received limited attention . With thuctivity ,35.The use of geophysical methods including electrical resistivity and induced polarization for delineating subsurface hydrostratigraphic heterogeneity has been validated in several studies ,37. AlsoThe objective of this study was to innovatively use standard geophysical methods i.e., electrical resistivity and induced polarization in combination with soil cores, to assess sites' suitability for establishing earthen fishponds. We showed the use of existing petrophysical relationships for predicting infiltration coefficients of the soil at each earthen fishpond site and assessing potential water seepages within them. We hypothesize that areas with high clay contents will correlate with low resistivity and high chargeability, have low infiltration rates, and retain water longer. Hence, they would be more suitable for establishing a fishpond. This study uses electrical resistivity and chargeability models of the study sites along with soil cores and petrophysical estimates of infiltration coefficient to characterize the soils and their potential to retain water. We, therefore, demonstrate the potential of using geophysics to address challenges beyond their traditional applications and contribute to addressing goals no. 1 and 2 of the United Nation's sustainable development goals ,41 for d2This study was conducted at a proposed fishpond site at Ugono-Abraka (Site-1) and an existing fishpond site at Agbarha-Otor (Site-2) communities in the Niger-Delta Region in Southern Nigeria. Site-1 is located between latitude 5.764–5.765° and longitude 6.142–6.144°, while Site-2 is located between latitude 5.5249–5.5255° and longitude 6.0685–6.0693° . The areThe topsoil in the study area, mostly at the Ugono-Abraka site, is mainly hydric soils consisting of a mixture of clay, silt, and sand, which creates seasonally inundated wetlands . The aqu3In this study, we used one-dimensional (1D) and two-dimensional (2D) distributions of electrical resistivity and induced polarization with soil cores to estimate the stratigraphic variations at the study sites. Electrical resistivity involves the injection of electrical current (I) using a pair of source electrodes and measuring the resulting potential difference (V) using other electrode pairs, while the resistivity (ρ) is estimated using Ohm's law and accounting for the electrode arrangement ,53. Indu3.1Field measurements of electrical resistivity and induced polarization were conducted using an ABEM Terrameter SAS 1000. A total of 10 vertical electrical soundings (VES) stations, with 5 at each test site, were acquired using the Schlumberger and dipole-dipole electrode arrays. Using a minimum AB/2-unit electrode spacing of 1 m with profile lengths ranging between 60 m and 120 m, 12 to 23 electrical soundings were acquired at each VES station. To minimize data error, a current injection of 1.00 mA was done with a minimum and maximum injection cycle of 3 and 6 following standards described in Ref. . We usedAlso, 5 transects of 2D electrical resistivity and chargeability were acquired using the same system and setup used for the electrical sounding data acquisition at the two study sites. Two transects were acquired at the Ugono-Abraka site and three at the Agbarha-Otor site . Due to 3.2Soil samples were collected to about 2.5 m depth at the proposed and existing fishpond areas for ground truthing the obtained geophysical models, which were later used to estimate the clay content and stratigraphic variation at the study sites. Static water levels were measured in surrounding boreholes and hand-dug wells (where available) with an electronic water level meter and a handheld Global positioning system (GPS) for each well location. Analysis of the measured water level was used to obtain an approximate groundwater flow direction map.f is given as:We measured the clay content in the soil from the collected field soil samples using a sedimentation test. We used the clay content to estimate the soil infiltration coefficients equation , relying. (2006) .44.14.1.1Selected 1D models of electrical resistivity and induced polarization (IP) for the first study site (Site-1 at Ugono-Abraka area) are shown in The 2D electrical resistivity and IP profiles , with re4.1.2The 1D electrical sounding sections for study site 2 (Agbarha-Otor area) show a 4- to 5-layer resistivity model with RMSE ranging between 2 and 3%. Selected electrical sounding results showing 1D electrical resistivity and IP are presented in Results of all 3 transects’ 2D electrical resistivity and IP are presented in 4.2f ranging from 0.05 to 9.5 m/day. For the study site at Agbarha-Otor, the clay content ranges from 0.3 to 1.6%, while the estimated infiltration coefficient kf ranges from 4.6 to 304.3 m/day.A summary of the estimated soil properties for both study sites, i.e., Ugono-Abraka and Agbarha-Otor, are presented in The static water levels measured from existing boreholes at study site 2 (Agbarha-Otor) were used to construct the relative groundwater flow direction shown in 55.1Electrical-sounding data obtained in this study were used to create a geoelectrical section with interpretations showing the possible corresponding lithology using resistivity values , Fig. 10The 2D IP results at site 1 , where a5.2Similar to the interpretation of site 1, we used results of the electrical resistivity and IP distributions to infer the shallow subsurface stratigraphy at site 2 (Agbarha-Otor). The 4- to 5-layer model in VES 1 to 5  is inter5.3f value of 38.88 m/day and Aweto and Akpoborie [f values ranging between 10.5 and 45.7 m/day.Based on the soil clay contents, we estimated the infiltration coefficient shown in kpoborie  with kf Estimates of the distribution of the soil properties obtained in this study can inform the design of the earthen fishponds . The pre6In this study, we showed the innovative use of non-invasive geophysical methods, including electrical resistivity and induced polarization to assess sites’ suitability for establishing earthen fishponds in the Niger Delta region of Nigeria. ID and 2D models of electrical resistivity and chargeability were combined with limited lithological data to delineate the shallow subsurface stratigraphy. We show the complimentary use of induced polarization with electrical resistivity for differentiating low resistivity clay zones from fluid content effect relying on the sensitivity of induced polarization, unlike resistivity mostly to the soil texture and less to the fluid content.We also showed the value of petrophysical relationships in characterizing sites with no prior hydraulic data by using existing petrophysical relationships to estimate the infiltration rates based on measured clay content. While such petrophysical relationships have inherent limitations, including their site-specific application, and should be used cautiously, they offer an approach for obtaining quantitative information on the site's hydraulic properties for this study. We calculated the infiltration coefficients based on the clay content to quantify potential percolation and the corresponding water retention at both study sites. Using the geophysical models of electrical resistivity and induced polarization to delineate the spatial extent of the clay layers at the sites provided an opportunity to spatially delineate zones with potentially low infiltration rates suitable for earthen fishponds.The results of this study revealed that the Ugono-Abraka site, where earthen fishing ponds are proposed, has subsurface conditions that are more suitable for earthen fishponds compared to that of Agbarha-Otor where there is an existing earthen fishing pond. This clay-rich layer at 3 – 5 m depth at the Ugono-Abraka site can restrict the vertical flow of water, allowing more water retention. While the results of this study provide insight into the hydrostratigraphic variability at the study sites, the interpretation is limited due to the lack of sufficient soil cores to adequately ground-truth the geophysical model. Future work is planned to extend the electrical resistivity and induced polarization models to 3D, collect soil samples, perform field hydraulic tests and develop a numerical model integrating the geophysical and hydraulic data to assess water retention capacity within proposed and existing earthen fishponds.Efemena Destiny Emmanuel; Edmund A. Atakpo: Conceived and designed the experiments; Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.Kennedy O. Doro: Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.Ruth E. Iserhien-Emekeme: Conceived and designed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data.Data will be made available on request.No additional information is available for this paper.This research received no external funding.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.