Homer1 isoforms, Homer1a and Ania-3, is thought to be related to processes of learning and memory. However, the precise regulation of Homer1a and Ania-3 with different components of learning has not been investigated. Here, we used in situ hybridization to quantify short and long Homer1 expression in the hippocampus following consolidation, retrieval, and extinction of associative fear memory, using contextual fear conditioning in rats. Homer1a and Ania-3, but not long Homer1, were regulated by contextual fear learning or novelty detection, although their precise patterns of expression in hippocampal subregions were dependent on the isoform. We also show for the first time that the two short Homer1 isoforms are regulated after the retrieval and extinction of contextual fear memory, albeit with distinct temporal and spatial profiles. These findings support a role of activity-induced Homer1 isoforms in learning and memory processes in discrete hippocampal subregions and suggest that Homer1a and Ania-3 may play separable roles in synaptic plasticity.Genes involved in synaptic plasticity, particularly genes encoding postsynaptic density proteins, have been recurrently linked to psychiatric disorders including schizophrenia and autism. Postsynaptic density Homer1 proteins contribute to synaptic plasticity through the competing actions of short and long isoforms. The activity-induced expression of short  Homer1 gene codes for a family of postsynaptic density proteins with key roles in the control of synaptic plasticity  dATP (PerkinElmer) then hybridized [Cornu Ammonis 1 (CA1), CA3, and dentate gyrus (DG)) was quantified as a measure of mRNA concentration.In situ hybridization is a method of localising and quantifying specific mRNA sequences in fixed tissue sections by hybridising with labelled strands of complementary nucleotide sequences. Coronal brain sections (14 bridized  to tissuPercent freezing was compared within subjects (learning phase) and between groups (euthanasia time) using two-way repeated measures analysis of variance (ANOVA). Main effects of behavioural intervention on mRNA expression within each hippocampal subregion were determined using independent one-way ANOVA tests. Post hoc Dunnett's multiple comparison procedure was applied to data which surpassed a significance threshold  in ANOVA, to determine specific group differences and directionality.Homer1, rats underwent a conditioning training trial. During contextual fear conditioning training, rats displayed robust postshock freezing, compared to baseline  = 19.47, P < 0.001; CA3 F = 7.13, P < 0.001; and DG F = 11.25, P < 0.001 and Ania-3: CA1 F = 27.08, P < 0.001; CA3 F = 3.03, P < 0.05; and DG F = 12.23, P < 0.001; one-way ANOVA, Figures Homer1 isoforms, as indicated by a pan-Homer1b/c/f/g oligonucleotide probe, was unchanged in all regions  = 0.47, P = 0.75; CA3 F = 0.31, P = 0.87; and DG F = 0.10, P = 0.98; one-way ANOVA, Arc expression, which has previously been shown to be coordinated with Homer1a in hippocampal circuits [ = 8.69, P < 0.001; CA3 F = 9.81, P < 0.001; and DG F = 6.93, P < 0.001; one-way ANOVA, Homer1a expression was increased in the CA1 region at 30 min, 2 h, and 4 h after conditioning and in the dentate gyrus at 30 min only. No changes in CA3 Homer1a expression were revealed in post hoc tests. In contrast, Ania-3 and Arc expression was increased in all three hippocampal regions, yet solely at the 30 min time point  = 15.42, P < 0.001; CA3 F = 7.75, P < 0.01; and DG F = 15.57, P < 0.001 and Ania-3: CA1 F = 10.25, P < 0.01; CA3 F = 4.33, P < 0.05; and DG F = 4.13, P < 0.05; one-way ANOVA) but not the long Homer1 isoforms  = 0.83, P = 0.46; CA3 F = 0.49, P = 0.62; and DG F = 1.55, P = 0.24; one-way ANOVA, Homer1 isoforms. Similarly to that seen previously, Homer1a and Ania-3 appeared to be induced at 30 min by contextual fear conditioning in each hippocampal subregion, although there was only a trend (P < 0.1) to an increase in Ania-3 expression in CA3 and the dentate gyrus in this experiment. Novel context exposure significantly increased Homer1a and Ania-3 expression in all regions. In all regions, there was no difference between the effects of conditioning or novel context exposure on the expression of Homer1a. There was no change in the expression of Long Homer1 with novelty or CFC training in any hippocampal subfield  or by the processes associated with the standard contextual fear conditioning paradigm such as novel stimulus presentation, we used a context preexposure facilitation effect (CPFE) procedure to further dissect the regulation of short Homer1 isoforms by associative fear learning. Training was split into three components: brief exposure (14–20 s) to a novel context with no presentation of the US (Brief Novelty); immediate footshock given upon exposure to a novel context (Novelty IS); and brief exposure to a familiar context with an immediate footshock (CPFE). Only the CPFE procedure is sufficient to generate an associative context-footshock fear memory [Homer1 gene expression to be similar to that observed following contextual fear conditioning previously, brains were only extracted 30 min after each behavioural intervention. There was a main effect of the group on Homer1a and Ania-3 expression within the CA1 region of the hippocampus  = 5.53, P < 0.01; and Ania-3: F = 4.60, P < 0.05; one-way ANOVA, Figures Homer1a expression was also modified in the dentate gyrus  = 5.19, P < 0.01), but was not significantly modified in CA3  = 2.47, P = 0.092). Ania-3 expression was unchanged in CA3  = 0.89, P = 0.46) and DG  = 0.38, P = 0.77). Post hoc Dunnett's tests on data from CA1 revealed that, compared to naïve controls, the expression of both Homer1a and Ania-3 was increased in the CA1 region following each stimulus, irrespective of context-footshock pairing, implying that the induction of short Homer1 isoforms did not depend on associative learning per se. There was a significant increase in the expression of Homer1a in CA3 and the dentate gyrus in the Novelty IS group but not the CPFE group. Thus, there is a lack of correlation in the regulation of Homer1a with associative CS-US learning in these two hippocampal subregions. In contrast, there were no significant changes in the expression of Ania-3 in either the CA3 or dentate gyrus with behavioural training. Therefore, there is dissociation between the transcriptional regulation of Homer1a and Ania-3 expression with associative learning in the hippocampal CA3 and dentate gyrus.To further examine whether r memory –62. SincLong Homer1 mRNA remained unchanged in all groups  = 0.88, P = 0.47; CA3 F = 1.79, P = 0.18; and DG F = 0.072, P = 0.97; one-way ANOVA, Consistent with expression in the standard contextual fear conditioning protocol, the levels of Homer1 isoforms are induced in the hippocampus by other associative learning processes, gene expression was quantified after the retrieval and extinction of contextual fear. All groups trained using the standard fear conditioning protocol displayed robust postshock freezing  = 492.9, P < 0.001, two-way repeated measures ANOVA) and extinction training induced a within-trial reduction of freezing  = 115.1, P < 0.001, two-way repeated measures ANOVA; Homer1a  = 28.78, P < 0.001; CA3 F = 4.98, P < 0.05; and DG F = 5.61, P < 0.01; one-way ANOVA) and Ania-3  = 11.64, P < 0.001; CA3 F = 9.04, P < 0.001; and DG F = 5.08, P < 0.05; one-way ANOVA) compared to “no recall” control subjects  = 38.83, P < 0.001; CA3 F = 13.82, P < 0.001; and DG F = 4.47, P < 0.05 and Ania-3: CA1 F = 24.00, P < 0.001; CA3 F = 5.91, P < 0.01; and DG F = 4.70, P < 0.05; one-way ANOVA). A significant retrieval-induced upregulation of Homer1a occurred at 30 min and 2 h in CA1 and CA3 and at 2 h only in the dentate gyrus. Ania-3 expression was upregulated at 30 min, but not 2 h, in all three hippocampal regions. The hippocampal expression pattern of each short Homer1 isoform following extinction learning mirrored that following retrieval. Long Homer1 expression was unchanged by context reexposure in any of the hippocampal subregions observed  = 1.40, P = 0.27; CA3 F = 0.91, P = 0.42; and DG F = 2.60, P = 0.098 and extinction: CA1 F = 2.42, P = 0.11; CA3 F = 3.22, P = 0.060; and DG F = 0.79, P = 0.47; one-way ANOVA).In order to investigate whether short subjects . A 10 miHomer1 isoforms in the hippocampus is correlated with experiencing a salient context, which may contribute to the formation or maintenance of Pavlovian associations. Within this, the relative expression of Homer1a and Ania-3 in different subregions of the hippocampus depended on the type of memory processing involved. Crucially, in some instances, the region-specific regulation of Homer1a differed to that of Ania-3. In addition, the temporal profiles of Homer1a and induction differed, with Ania-3 expression having a more curtailed profile. Long forms of Homer1, which were targeted as a group with one oligonucleotide probe, were not regulated by contextual fear conditioning, retrieval, or extinction or stimulus-driven experience in any hippocampal subregion or time point measured, consistent with its previously reported constitutive expression [The present findings indicate that the expression of short pression .Homer1 isoforms in the CA1 is consistent with its role as a key region for the consolidation of contextual fear (CS-US) memory [Homer1a and Ania-3 in CA1 is also driven by novelty. The direct monosynaptic pathway from the entorhinal cortex conveys inputs from sensory systems to CA1 and to serve novelty detection [Homer1 isoforms may correlate with the contribution of novelty to the comparator function of CA1 and the encoding of memory [Homer1a functions to potentiate synaptic transmission  and is r) memory , 69. Mor) memory –73. Our etection . As suchf memory .Homer1a and Ania-3 in the CA3 and dentate gyrus after contextual fear conditioning and novelty exposure is more likely to be related to the Pavlovian associative events of contextual memory formation. The formation of conjunctive spatial or contextual representations is necessary for the formation of an association between a stimulus and a context (CS-US association) [Homer 1a and Ania-3 expression in the dorsal CA3 and dentate gyrus are thus consistent with the role of these hippocampal subregions in the formation of contextual representation [Homer1a, but not Ania-3, in CA3 and the dentate gyrus. However, the observation of short Homer1 expression at additional time points may reveal a different pattern of induction. The possibility that Ania-3 may have a more restrictive role in the formation of contextual memory also demands further investigation.The regulation of ciation) –81. Howeentation , 83. TheHomer1a and Ania-3 expression after contextual fear conditioning exhibited striking temporal differences. This was reflected in the duration for which the elevated expression level was detectable. Regulated Ania-3 expression was considerably more transient than Homer1a in all hippocampal subregions. This observation, which is previously unreported, implies that these two activity-induced isoforms are regulated through different transcriptional and/or posttranscriptional mechanisms. It is possible that this discrepancy occurs due to differences in metabolic processing, yet may also have implications for the function of the translated proteins. Coincident regulation of Homer1a and Arc in the hippocampus has been previously reported [Homer1a and Arc with contextual fear conditioning, in terms of a temporal profile, the expression of Ania-3 more closely parallels the expression of Arc. Based on the current observations, it may be hypothesised that whilst these synaptic proteins may function in concert in the structural and synaptic modifications supporting memory formation, there is a closer association of Ania-3 and Arc-mediated processes.The regulation of reported . Whilst Homer1a and Ania-3 in all three hippocampal subfields after conditioned context cued recall, whether the recall period was short (2 min) or long (10 min). These changes reflect the coordinated activity of the hippocampal subregions in the retrieval of contextual fear memory [Homer1 isoforms after contextual fear memory retrieval may be related to the hippocampal-dependent memory processes of reconsolidation and extinction associated with short and prolonged conditioned context exposure, respectively [Homer isoforms in retrieval-related memory processes, including extinction learning, has been presented. It also implicates Homer1 in specific cognitive processes relevant to psychiatric disorders [We observed an increase in the expression of both r memory , 85. Simr memory –88. The ectively , 89, 90.ectively –93. Thisisorders .Homer1 variants are expressed not only following the consolidation of contextual fear memories but also accompanying their retrieval and extinction. We also demonstrate for the first time that Homer1a and Ania-3 are differentially regulated both temporally and spatially in the hippocampus during fear learning processes and therefore may have different roles in the regulation of long-term contextual fear-memory associations.In conclusion, the present results build on previous studies showing that short, activity-induced Homer1 immediate early genes are involved in learning and memory. We present novel findings showing that these short


The most frequently detected compounds were p,p′-DDD and chlorpyrifos. The order of contamination was spinach > cabbage > onions. Generally, there were no significant variations in concentrations of pesticide residues among samples and sampling sites, which indicated similarities in contamination patterns. The concentrations of contaminants were above the maximum residue limits (MRLs) in 33.3–50% of the samples. The findings indicated risks and concerns for public health. This study investigated the levels of pesticides and metabolites in vegetables from major markets in Dar es Salaam city, Tanzania. Samples of fresh cabbage, spinach, and onions from the markets were analysed for pesticide residues. Extraction was performed using acetone followed by dichloromethane : cyclohexane mixture and the extracts were cleaned up using Florisil. The compounds were determined by gas chromatography-mass spectrometry (GC-MS). Pesticides and metabolites were detected in 72.2% of the samples. The detected pesticide residues and their highest mean concentrations were Pesticides are widely used in vegetables to control pests and diseases during farming, transportation, and storage. Pesticides are known to be the most important tool for the production of adequate food supply for an increasing world population and for the control of vector-borne diseases . HoweverVegetables are among the most frequently consumed food types in Tanzania. As vegetables are eaten either fresh or semiprocessed and due to improper agricultural practices of some farmers such as not observing the withholding periods after spraying, it could be expected that they contain high pesticide residues. Dar es Salaam is a big city hosting major transportation and commercial networks, markets, and industrial activities. The largest and busiest markets in Tanzania are found in Dar es Salaam. These markets are well known for their massive sales of vegetables that come from different areas of the country where pesticides are widely used. Thus, assessment of pesticides in samples from these markets could reflect the contamination status in the area and other areas. Literature surveys indicated that no study had been conducted on pesticide residues in vegetables in Tanzanian markets. Therefore, the above observations prompted the inception of this study.Four major markets of Dar es Salaam city were randomly selected for collection of vegetables in December 2013. The samples were collected from Kariakoo (Kko), Buguruni (Bgn), Mwananyamala (Mny), and Temeke (Tmk) markets in Dar es Salaam region. All these markets are common selling places for vegetables and the vegetables come from different regions of Tanzania.  Brassica oleracea var. capitata (cabbage), Spinacia oleracea (spinach), and Allium cepa (onions). Sampling was conducted by applying standard guidelines [The selected vegetables collected wereidelines . A totalSample preparation and extraction were conducted within 24 hours after sampling. Each sample was homogenized by using motor and pestle. The homogenized sample (20 g) was extracted with acetone (20 mL) and then with a mixture of dichloromethane : cyclohexane  by sonication in ultrasonic bath for 30 min. The mixture was filtered through glass wool containing anhydrous sodium sulfate for drying. The sodium sulfate was then washed with dichloromethane : cyclohexane . The extract was concentrated in rotary evaporator operated at 40°C and made up to 2 mL in cyclohexane [The clean-up procedure for extracts was conducted according to Åkerblom (1995) with some modifications. A chromatographic tube of 10 mm i.d. × 32 cm was plugged with glass wool, packed with activated Florisil (3 g), and topped up with sodium sulfate (5–10 cm). The column was rinsed with cyclohexane (5 mL), and then the extract (2 mL) was passed through the column and eluted sequentially with cyclohexane (20 mL) and cyclohexane : acetone . The collected portions were combined and concentrated in rotary evaporator to 2 mL in cyclohexane : acetone (9 : 1).α,5,8,8α-hexahydro-exo-1,4-endo-5,8-dimethanonaphthalene), dieldrin , p,p′-DDT  ethane), o,p′-DDT -2-(4-chlorophenyl) ethane), p,p′-DDD  ethane), o,p′-DDD -2-(4-chlorophenyl) ethane), p,p′-DDE  ethene), o,p′-DDE -2-(4-chlorophenyl) ethene), α-endosulfan, β-endosulfan, α-HCH , β-HCH , γ-HCH , and δ-HCH . The organophosphorus pesticides were chlorpyrifos , fenitrothion -phosphorothioate), and pirimiphos methyl (O-(2-diethylamino-6-methylpyrimidin-4-yl)O,O-dimethyl phosphorothioate) and the pyrethroid pesticide was cypermethrin ((RS)-α-cyano-3-phenoxybenzyl-3--2,2-dimethylcyclopropane carboxylate).The analytes studied included fourteen (14) organochlorine compounds, three (3) organophosphorus pesticides, and one (1) pyrethroid pesticide. The organochlorine compounds were aldrin . The glassware was cleaned with water and detergent and then with distilled water and rinsed with acetone. Other tools were also thoroughly cleaned before and after use. Sodium sulfate was heated at 130°C for 2 hours in order to remove moisture, and Florisil was preheated at 130°C overnight and partially deactivated with 5% distilled water. Pesticides standard solutions were of high purity . Working standard solutions were prepared at concentrations ranging from 0.5 to 2 μm), and an autosampler. The initial temperature programme was 90°C, held for 2 min. The temperature was then ramped up to 260°C at 5°C/min and held for 5 min. The injector temperature was 250°C. The carrier gas was helium at the flow rate of 2.17 mL/min with average velocity of 54.6 cm/sec. The GC-MS was operated in splitless mode with a purge flow of 3 mL/min; the injection volume was 1 μL and the pressure was set at 150 kPa. The GC interface temperature was 300°C. The mass spectrometer was operated in electron impact (EI) ionisation at 0.2 V with ion source temperature of 230°C and in full scan mode with the range of 45–500 m/z. Standards were analysed on each day of analysis. Analysis was carried out in replicates (duplicates) and a total of 24 samples were analysed for each sample type (matrix).Sample analysis was done at Chemistry Department, University of Dar es Salaam. The compounds were determined using a gas chromatograph coupled to a mass spectrometer (GC-MS). The analyses were performed using a Shimadzu GC-MS QP 2010 Ultra equipped with MSD, fused silica capillary column Rtx-5MS (30 m × 0.25 mm × 0.25 m/z) of analytes are given in The identification of the compounds was accomplished by comparing the retention times and mass spectra of analytes in samples to those of reference standards run at the same conditions with the samples. The analytes were also identified using the NIST 11 mass spectral library . A specific pesticide was identified if it had the same retention time to that of the standard (within a deviation of ±0.05 min) and their spectra matched. Selected mass spectra of analytes are presented in Statistical analysis of the data was performed by using GraphPad Instat software . The dat p,p′-DDT, p,p′-DDD, o,p′-DDD, endosulfans, chlorpyrifos, and cypermethrin. Other pesticide residues analysed  were below the detection limits. Among the analysed pesticide residues, the following residues were detected in cabbage: p,p′-DDD was the most frequent pesticide residue although its concentrations in samples were generally low (up to (1.10 ± 0.20) × 10−2 mg/kg). Other DDT residues included p,p′-DDT which was detected in samples from one site with mean concentration of 4.00 × 10−3 mg/kg and o,p′-DDD was also detected in samples from one site with mean concentration of 1.00 × 10−3 mg/kg. The concentrations of total DDT (DDT + DDD + DDE) were up to 1.20 × 10−2 mg/kg. The DDD was found to appear in most samples (83.3%) while the DDE isomers were not detected. This suggested that the degradation of DDT was dominated by anaerobic pathway. DDD is a metabolite of DDT under anaerobic degradation, in which case irrigation water can create anaerobic environment [Among the organochlorines detected in cabbage samples,ironment . The DDTα-endosulfan and β-endosulfan were detected in 33.3% of the samples and their concentrations were up to (6.00 ± 0.1) × 10−1 mg/kg and (2.10 ± 0.03) × 10−1 mg/kg, respectively. The concentrations of α-endosulfan were higher than β-endosulfan in all samples. This suggests recent inputs of fresh technical endosulfan or lack of significant degradation [The compounds radation , 9. The radation  on pesti−2 mg/kg, detected from Temeke samples. Cypermethrin is nonpersistent pesticide; it degrades easily in the presence of sunlight and water and this explains the detection of low levels in cabbage samples.Three types of organophosphorus pesticides  were analysed in cabbage of which only chlorpyrifos was detected in 33.3% of the samples. The highest concentration of chlorpyrifos was 2.40 ± 0.04 mg/kg. The concentrations of chlorpyrifos were higher than other pesticide residues obtained. This can be explained by the fact that chlorpyrifos is a pesticide which is legalised for use in horticulture production ; thus itThe findings of this study are comparable to the findings of the study conducted by Munawar and Hameed  on cabbaThe concentrations of pesticide residues were compared to the maximum residue limits (MRLs) set by FAO and WHO , which r p,p′-DDD, o,p′-DDD, endosulfans, chlorpyrifos, and cypermethrin. Other pesticide residues analysed  were not detected in all samples. The following pesticide residues were detected in spinach: p,p′-DDD with detection frequency of 75%, followed by endosulfan (33.3%) and o,p′-DDD (16.7%). The maximum concentration of p,p′-DDD was (6.40 ± 0.07) × 10−1 mg/kg. The highest concentration of total DDT was 6.50 × 10−1 mg/kg. The trend of DDT and its metabolites was the same as in cabbage samples. In Tanzania, the use of DDT has been prohibited for many years, but it is still in use for controlling malaria. On the other hand, DDT and its metabolites are persistent organic pollutants (POPs) and they remain in the environment for long periods; it is therefore not surprising to find residues of these pesticides in this study.The most frequent organochlorine pesticide residue detected in spinach wasα-endosulfan and β-endosulfan in spinach were (2.40 ± 0.20) × 10−1 mg/kg and (8.00 ± 0.40) × 10−2 mg/kg, respectively. The concentrations of α-endosulfan were higher than β-endosulfan; this represents technical formulation, which suggests recent inputs or lack of significant degradation [ Amaranth spp. from field areas in Tanzania reported concentrations of endosulfans of up to 1.69 mg/kg [The highest concentrations of radation . Currentradation . These cradation . The stu−2 mg/kg.Chlorpyrifos was the only organophosphorus pesticide detected in 41.7% of the spinach samples. The highest concentration of chlorpyrifos was 3.00 ± 0.20 mg/kg. As in cabbage, the concentrations of chlorpyrifos were found to be higher than the concentrations of other pesticide residues obtained; this indicates the fresh use of chlorpyrifos with lack of significant degradation. Cypermethrin was detected in 33.3% of the spinach samples and the highest concentration was (4.00 ± 0.20) × 10 Amaranths spp. in Tanzania by Meela [The results obtained from this study show that the concentrations of chlorpyrifos were far above the concentrations obtained by Munawar and Hameed  who founby Meela  did not Most of the concentrations of DDD residues in spinach were below the MRL while their concentrations in one sample were above the MRL of 0.2 mg/kg by 3.2 times. The concentrations of cypermethrin in all spinach samples were below the MRL. The concentrations of endosulfans and chlorpyrifos significantly exceeded the MRLs in all samples in which they were detected. The concentrations of endosulfan were 3.8–6.4 times greater than the MRL of 0.05 mg/kg, while those of chlorpyrifos were 2.6–6 times greater than the MRL of 0.5 mg/kg . In gene p,p′-DDD, α-endosulfan, β-endosulfan, chlorpyrifos, and cypermethrin were detected in 16.7–50% of the onion samples. α-HCH, β-HCH, γ-HCH, δ-HCH, p,p′-DDT, o,p′-DDT, o,p′-DDD, o,p′-DDE, p,p′-DDE, aldrin, dieldrin, fenitrothion, and pirimiphos methyl) were not detected.Among the analysed pesticide residues, p,p′-DDD, α-endosulfan, and β-endosulfan. The concentrations of p,p′-DDD were very low, with maximum concentration of 1.02 × 10−2 mg/kg. Endosulfans were only detected in the samples collected from one market (Temeke). The highest concentrations of α-endosulfan and β-endosulfan were (2.20 ± 0.02) × 10−1 mg/kg and (7.00 ± 0.30) × 10−2 mg/kg, respectively. The concentrations of α-endosulfan were greater than those of β-endosulfan; this indicates the fresh use of technical endosulfan without significant degradation [The organochlorine pesticide residues detected in onion samples wereradation , 9. The radation  in onion−2 mg/kg. The mean concentration of chlorpyrifos were higher than the levels obtained by Bempah et al. [Among the organophosphorus pesticide residues analysed in onion samples, only chlorpyrifos was detected in 25% of the samples and the highest concentration was 2.12 ± 0.10 mg/kg. Cypermethrin (pyrethroid) was detected in 16.7% of the samples and its highest concentration was (1.40 ± 0.04) × 10h et al.  in onionAll the concentrations of DDD residues in onions were below their MRL of 0.2 mg/kg set by FAO and WHO . The con o,p′-DDT, o,p′-DDE, p,p′-DDE, aldrin, dieldrin, fenitrothion, pirimiphos methyl, and all of the HCH isomers  were not detected in all samples. This suggested that they were not used for the vegetables studied or there was no significant contamination due to these compounds.There were variations in occurrence of DDT residues among the types of samples; they appeared most frequently in cabbage samples (83.3%) followed by spinach samples (75%) and onions (50%). In terms of occurrence of endosulfans, there were no variations in detection frequencies between spinach and cabbage samples (33.3%) while onions had the lowest detection frequency (16.7%). Chlorpyrifos most appeared in spinach samples (41.7%) followed by cabbage samples (33.3%) and finally onions (25%). The occurrence of cypermethrin varied in the order spinach > cabbage > onion samples, with detection frequencies of 33.3%, 25%, and 16.7%, respectively. Generally, 72.2% of the samples contained pesticides and metabolites. The compoundsThere were slight variations in the concentrations of total DDT among all the sample types and the highest mean concentration was observed in spinach while the lowest was found in onion samples. There were slight variations in the levels of endosulfans; the highest mean concentration was found in cabbage samples and the lowest mean concentration was in onion samples. The highest mean concentration of chlorpyrifos was observed in spinach and the lowest in onion samples. For the levels of cypermethrin, spinach samples had the highest mean concentration while onion samples had the lowest. The concentrations of chlorpyrifos were the highest among the pesticide residues detected in the samples. p = 0.6634 to KW = 5.065 at p = 0.0795; number of points = 12 in each sample type). Generally there were no significant variations of all pesticide residues among the vegetables. This suggests that there were no significant differences in the farming conditions as well as the application or contamination patterns of the pesticides and maybe the vegetables investigated have similar pesticides absorption or accumulation abilities.Statistically, there were no significant variations in concentrations of the pesticide residues among the cabbage, spinach, and onion samples at 95% confidence level . These results indicate that most vegetables from all the markets have similar sources; they possibly come from similar places or regions.There were no significant differences in the concentrations of pesticide residues among the sampling sites: KW = 3.256,  p,p′-DDT, p,p′-DDD, o,p′-DDD, α-endosulfan, β-endosulfan, chlorpyrifos, and cypermethrin. Their detection frequencies varied from 8.3% to 83.3%. The highest mean concentrations of total DDT, total endosulfan, and α-HCH were 6.50 × 10−1 mg/kg, 8.10 × 10−1 mg/kg, and 4.00 × 10−3 mg/kg, respectively. The mean concentrations of chlorpyrifos and cypermethrin were up to 3.00 mg/kg and 4.00 × 10−2 mg/kg, respectively. The profiles of DDT residues suggested past use dominated by anaerobic degradation forming p,p′-DDD. The concentrations of α-endosulfan were higher than the concentrations of β-endosulfan in all samples in which they were detected indicating contamination with fresh technical endosulfan. Residues of two or more pesticides were commonly found in the vegetables. The cooccurrence of pesticide residues in samples was due to various reasons including mixing of pesticides by farmers during application as farmers use more than one pesticide at one time due to resistance of pests. Other reasons could be due to contamination through water, soil, and air. There were no significant variations of the concentrations of pesticide residues among the vegetables suggesting similar contamination sources or patterns. The levels of pesticide residues were above the MRLs in 41.7% of cabbage samples, 50% of spinach samples, and 33.3% of onion samples. The samples could pose health hazards to the consumers. Therefore, it is recommended that effective monitoring of pesticide residues in food items is required.Seven pesticide residues were detected, which were


Natural sounds convey perceptually relevant information over multiple timescales, and the necessary extraction of multi-timescale information requires the auditory system to work over distinct ranges. The simplest hypothesis suggests that temporal modulations are encoded in an equivalent manner within a reasonable intermediate range. We show that the human auditory system selectively and preferentially tracks acoustic dynamics concurrently at 2 timescales corresponding to the neurophysiological theta band (4–7 Hz) and gamma band ranges (31–45 Hz) but, contrary to expectation, not at the timescale corresponding to alpha (8–12 Hz), which has also been found to be related to auditory perception. Listeners heard synthetic acoustic stimuli with temporally modulated structures at 3 timescales  and identified the stimuli while undergoing magnetoencephalography recording. There was strong intertrial phase coherence in the theta band for stimuli of all modulation rates and in the gamma band for stimuli with corresponding modulation rates. The alpha band did not respond in a similar manner. Classification analyses also revealed that oscillatory phase reliably tracked temporal dynamics but not equivalently across rates. Finally, mutual information analyses quantifying the relation between phase and cochlear-scaled correlations also showed preferential processing in 2 distinct regimes, with the alpha range again yielding different patterns. The results support the hypothesis that the human auditory system employs (at least) a 2-timescale processing mode, in which lower and higher perceptual sampling scales are segregated by an intermediate temporal regime in the alpha band that likely reflects different underlying computations. Correctly perceiving behaviorally significant sounds—speech, music, and the acoustic environment—requires integrating acoustic information over time to extract relevant regularities. A fundamental question about this process is: How does the auditory brain integrate information of continuously varying sounds, typical of many natural auditory signals? How does the brain “sample” the input? To investigate this question, we measured how cortical activity is entrained by sound using the noninvasive technique magnetoencephalography. We presented sounds with temporal structure at different timescales and examined how the brain encodes such signals. We found, unexpectedly, that the human auditory system does not treat all rates equally but predominantly uses 2 nonoverlapping timescales, the slower (theta) and faster (gamma) bands, to track acoustic dynamics, while the timescale corresponding to an intermediate  timescale is likely reserved for other cortical operations, perhaps relating to attention and functional inhibition. The data support the hypothesis that the human auditory system employs (at least) a 2-timescale processing mode and that the perception of natural sounds, which feels seamless and continuous, is underpinned by segregated and discontinuous neural processing. Speech, music, and many natural sounds have a rich temporal structure over multiple timescales –5; such Behavioral research suggests that the human auditory system may optimize processing by operating within separate temporal ranges instead of in a unitary way across a continuum of temporal variation –15. TimeHere, we investigate whether these very clear behavioral results arguing for distinct timescales could be illuminated, especially in terms of their neural implementation, by considering cortical oscillations. Cortical oscillations reflect rhythmic activity of neural populations at different scales ,28, and Of course, sounds contain information in ranges lying between these well-separated temporal regimes. Is there really such a compelling segregation of function in the time domain? Apart from the 2 timescales mentioned above, cortical oscillations within the alpha band (8–12 Hz) have been found in many studies to critically correlate with auditory attention –35, audiStudies using amplitude-modulated sounds or click trains have shown a low-pass modulation transfer function (MTF) with a rebound above 30 Hz –45. AlthIn studies using speech stimuli with irregular and complex modulations, it has been found that theta band activity entrains to the envelope of speech , and that phase locking in the theta band is enhanced by increased speech intelligibility –54. DiffHere, we aimed to elucidate what kind of mechanism might form the basis of such multiscale hearing by using irregular temporal modulations of auditory signals to ask whether neural oscillations are entrained equally to auditory stimuli of different irregular modulation rates or, rather, only specific, restricted bands; moreover, we asked whether different stimulus modulation rates can be decoded from specific neural frequency bands. We focus on cortical oscillations in the theta and gamma bands as well as the alpha band, in which strong effects related to auditory processing have been reported ,64.Building on experiments by Boemio et al. (2005)  and Luo We first examine how well listeners can recognize stimuli with varying frequency modulation rates, including especially rates that correspond to theta, alpha, and gamma band periods. The behavioral sensitivity to different modulation rates provides a first indication whether specific rates are preferred by the human auditory system.α) sound, and the stimulus type with modulation rate in the gamma band range (30–45 Hz) as a gamma (γ) sound. The cochleograms of 3 sounds are shown in θ, α, and γ sounds by button press. Sounds were presented either as clean stimuli or presented in noise at various SNRs. The results  as a theta (θ) sound, the stimulus type with modulation rate in the alpha band range (8–12 Hz) as an alpha  = 9.78, p = 0.001, ηp2 = 0.411). Planned comparisons using paired t tests reveal that the identification of α sounds was significantly worse than the identification of the other 2 stimuli  = −3.16, p = 0.021, d = −0.82; comparison to γ sound, t(14) = −4.95, p = 0.001, d = −1.28; Bonferroni corrected). There was no difference in identification performance between the θ and γ sounds (t(14) = 0.65, p > 0.05, d = 0.17).The behavioral performance in identifying the 3 clean stimuli was analyzed using a 1-way repeated measures ANOVA (rmANOVA) with Stimulus-type as the main factor. There is a main effect of Stimulus-type  = 17.60, p < 0.001, ηp2 = 0.557) and SNR  = 144.86, p < 0.001, ηp2 = 0.912) as well as a Stimulus-type × SNR interaction  = 2.47, p = 0.017, ηp2 = 0.150). A quadratic trend analysis indicates that identification of stimuli decreased as SNR decreases  = 510.35, p < 0.001, ηp2 = 0.973).For the masked stimuli, a Stimulus-type × SNR 2-way rmANOVA reveals main effects of Stimulus-type (z-scores of ITC (zITC).  across all frequencies from 2 Hz to 50 Hz and in a time range from 300 ms to 1,800 ms after the onset of the stimuli to measure how oscillatory cortical activity in each frequency band responds to different modulation rates. ITC measures the robustness of neural responses to stimuli across trials. If cortical oscillations at a certain frequency band reliably respond to a specific stimulus , we would obtain high ITC values at this frequency band. We created a distribution of ITC values by randomizing the onset time of each trial to normalize ITC in each subject across all frequencies and we converted the original ITC to θ sounds and that the neural gamma band (31–45 Hz) is strongly coherent to γ sounds. Unexpectedly, the alpha band (8–12 Hz) reveals no selective response to the temporally corresponding stimuli. However, the α and γ sounds also evoked robust phase coherence at a frequency range below 8 Hz, in which zITC of the group means for α and γ sounds are above 1.64—the critical z-score equivalent to an alpha level of 0.05 .The zITC values for the clean stimuli across all frequencies are plotted in θ sounds in the theta band and for γ sounds in the gamma band. Such auditory response patterns, though weak, were also observed in the theta band for α and γ sounds.Crucially, no robust phase coherence was found in the alpha and beta bands. This nonuniform phase-response pattern across temporal regimes does not support the simplest hypothesis of comparable neural tracking for all stimulus modulation rates. Consistent results were obtained in the spatial analysis. The topographies of zITC, as shown in F = 3.88, p = 0.033, ηp2 = 0.217) and Frequency band  = 30.50, p < 0.001, ηp2 = 0.685) as well as an interaction between Stimulus-type and Frequency band  = 3.67, p = 0.003, ηp2 = 0.208). The main effect of Hemisphere was not significant  = 0.22, p = 0.648, ηp2 = 0.015).To measure the effects of different stimuli on zITC, a Stimulus-type × Hemisphere × Frequency band 3-way rmANOVA was performed. This revealed main effects of Stimulus-type (t tests with Bonferroni correction on the main effect of Stimulus-type show that zITC of θ sounds is larger than zITC of α sounds (t(14) = 3.36, p = 0.014, d = 0.87). Post hoc analysis of the main effect of Frequency band with Bonferroni correction shows that zITC at the theta band is larger than the alpha band (t(14) = 7.39, p < 0.001, d = 1.91), beta band (t(14) = 9.47, p < 0.001, d = 2.45), and gamma band (t(14) = 7.43, p < 0.001, d = 1.92) and that zITC at the alpha band is larger than the beta band (t(14) = 3.52, p = 0.021, d = 0.91).Planned post hoc comparisons using paired θ sounds is larger than both zITC of α sounds (t(14) = 4.00, p = 0.007, d = 1.14) and γ sounds (t(14) = 3.86, p = 0.010, d = 1.00); in the gamma band, zITC of γ sounds is larger than zITC of α sounds (t(14) = 2.93, p = 0.044, d = 0.76). Before adjusted FDR correction, zITC of γ sounds is significantly larger than θ sounds at the gamma band (t(14) = 2.20, p = 0.022, d = 0.57). There are no significant differences of zITC across different sounds found in the alpha and beta bands after adjusted FDR correction.Post hoc analyses on Stimulus-type × Frequency band interactions using adjusted false discovery rate (FDR) correction ,68 show θ, α, and γ sounds evoke robust phase coherence in the frequency bands other than their corresponding frequency bands, a 1-sample t test of zITC in comparison with a baseline of 1.64 was conducted in each frequency band for each sound. zITC above 1.64 means that the phase coherence observed is above the 95th percentile of ITC distribution over trials of randomized onset time. After adjusted FDR correction, we found robust phase coherence in the theta band for θ sounds (t(14) = 38.06, p < 0.001, d = 9.82) and for γ sounds (t(14) = 3.01, p = 0.028, d = 0.78) but not for α sounds (t(14) = 1.66, p = 0.240, d = 0.43). There are no significant results in alpha, beta, and gamma bands. zITC of γ sounds in the gamma band is not significant (t(14) = −0.15, p = 1.00, d = −0.03), likely because robust phase coherence peaks within a narrow frequency range centered around 37 Hz, as shown in the spectrum of zITC in γ sound from 30 to 45 Hz decreases the mean of zITC in the gamma band.To investigate whether γ sounds whose modulation rate is in the gamma band range. zITC for α sound in the theta band also shows phase coherence, although it is not significantly above threshold.To summarize this first set of analyses, we showed that cortical oscillations in the theta and gamma bands, but not in the alpha band, robustly entrained to sounds with modulation rates in the corresponding frequency ranges. The further analysis of zITC indicates that theta band oscillations reliably respond to θ, α, and γ sounds.This preferential 2-scale (theta and gamma) response pattern of the cortical auditory system shown by phase coherence results aligns with the findings in neurophysiology related to speech perception and production   = 4.29, p = 0.024, ηp2 = 0.234) and Frequency band  = 28.84, p < 0.001, ηp2 = 0.673) as well as an interaction between Stimulus-type and Frequency band  = 2.88, p = 0.013, ηp2 = 0.171). The main effect of Hemisphere was not significant  = 0.33, p = 0.575, ηp2 = 0.023).A Stimulus-type × Hemisphere × Frequency band 3-way rmANOVA was performed and revealed main effects of Stimulus type (t tests with Bonferroni correction on the main effect of Stimulus-type show that the evoked power of θ sounds was larger than that of α sounds (t(14) = 3.58, p = 0.009, d = 0.92). Post hoc analysis of the main effect of Frequency band showed that the evoked power in the theta band is larger than that in the alpha band (t(14) = 3.88, p = 0.010, d = 1.00), in the beta band (t(14) = 8.84, p < 0.001, d = 2.28), and in the gamma band (t(14) = 5.14, p < 0.001, d = 1.33). Evoked power in the alpha band is larger than the beta band (t(14) = 5.23, p < 0.001, d = 1.35), and evoked power in the gamma band is larger than beta band (t(14) = 6.32, p < .001, d = 1.64).Post hoc paired θ sounds is larger than the evoked power of α sounds (t(14) = 4.77, p < 0.001, d = 1.23) and γ sounds (t(14) = 3.32, p = 0.020, d = 0.86). In the gamma band, the evoked power of γ sounds is larger than the evoked power of α sounds (t(14) = 3.94, p = 0.006, d = 1.02). There is no significant difference between evoked power across different sounds found in alpha and beta bands after adjusted FDR correction.A post hoc analysis of the Stimulus-type × Frequency band interaction using adjusted FDR correction shows that, in the theta band, the evoked power of F = 15.36, p < 0.001, ηp2 = 0.523). A post hoc analysis with Bonferroni correction showed that the power at the beta band was less than the theta band (t(14) = 6.88, p < 0.001, d = 1.78), alpha band (t(14) = 5.26, p = 0.001, d = 1.36), and gamma band (t(14) = 5.77, p < 0.001, d = 1.49). There is no difference in power between theta, alpha, and gamma bands. The main effect of Hemisphere was marginally significant  = 4.51, p = 0.052, ηp2 = 0.244), with the power in the right hemisphere larger than in the left hemisphere.Power responses induced by the different stimuli were explored by a Stimulus-type × Hemisphere × Frequency band 3-way rmANOVA. The main effect of Frequency band was significant . A Pearson’s correlation was then calculated for these values between each adjacent time point. The cochlear-scaled correlation for each sound is shown in θ sounds (p < 0.05) and significant main effects of the phase sound type between 33 and 39 Hz using the cochlear-scaled correlation of γ sounds. Importantly, no significant main effects of the phase sound type were found for mutual information computed using the cochlear-scaled correlation of α sounds. In the post hoc comparison with Bonferroni correction, we averaged mutual information within the frequency ranges in which significant main effects were observed and found that, when the cochlear-scaled correlation of θ sounds was used, the mutual information computed using phase series of θ sound is significantly larger than that using phase series of α sound (t(14) = 5.29, p < 0.001, d = 1.37) and that using phase series of γ sound (t(14) = 3.97, p = 0.004, d = 1.03). When the cochlear-scaled correlation of γ sounds was used, the mutual information computed using phase series of γ sound is significantly larger than that using phase series of θ sounds (t(14) = 5.05, p < 0.001, d = 1.30) and that using phase series of α sounds (t(14) = 5.71, p < 0.001, d = 1.47).We ran a 1-way rmANOVA on mutual information with the factor of phase responses evoked by sound type (phase sound type). After adjusted FDR correction across frequencies, we found significant main effects of the phase sound type between 4 and 6 Hz using the cochlear-scaled correlation of θ sounds and that in the gamma band for γ sounds is indeed caused by tracking specific acoustic structures, rather than simply being evoked by generic acoustic stimuli. The fact that no significant results were found for α sounds suggests, again, that the alpha band may play a different role in processing sounds, and especially their temporal structure. In contrast, the theta band and the gamma band may be central to auditory processing and the construction of neural representations underlying perceptual analysis.The results of the mutual information analyses demonstrate that phase patterns in the theta and gamma bands track the temporal structure of the stimuli, as quantified by the cochlear-scaled correlation. The robust phase coherence observed in the theta band for γ sounds in the theta band, although γ sounds evoked robust phase coherence in the theta band . We further explored the contribution of the theta band to coding temporal information of γ sounds in the following classification analyses.We did not find specialized tracking for eta band . This coθ, α, and γ sounds, it implies that the theta band plays an important role in processing θ, α, and γ sounds. On the other hand, if a frequency band does not contribute to classifying any sounds, it may indicate that this frequency band is not a key component to processing the sounds.We next performed classification analysis to investigate whether information in each frequency band of cortical oscillations can be used to classify different stimulus types. If a frequency band, for example, the theta band, reflects sufficient information to classify We first use phase and power responses in a frequency range of 4–45 Hz and a time range of 300–1,900 ms  for classification to test whether phase or power provide information related to the temporal structure of each sound. Second, we measure the contribution of each frequency band in classification to determine which frequency band is by hypothesis critical to auditory processing. Finally, we use a new method to classify stimulus type at each time point to investigate temporal progression of the classification performance.d′ in the behavioral results), are shown in F = 30.44, p < 0.001, ηp2 = 0.685), with the D′ of phase-based classification significantly larger than the D′ of power-based classification. To determine whether classification performance is better than chance (D′ = 0), a 1-sample t test with Bonferroni correction was applied on each stimulus type and each classification source. For phase classification, the performance of all stimulus types was better than chance  = 6.19, p < 0.001, d = 1.60; for α sounds, t(14) = 6.40, p < 0.001, d = 1.65; for γ sounds, t(14) = 6.44, p < 0.001, d = 1.66). For power classification, classification performance of α sounds was significant (t(14) = 4.73, p = 0.002, d = 1.22) as well as θ sounds (t(14) = 3.10, p = 0.046, d = 0.80), but performance of power classification was only slightly above chance. These results demonstrate that phase patterns of cortical oscillations reliably encode the temporal dynamics of stimuli.Classification performance was first computed for each stimulus type using the phase and power response profile of all frequency bands (4–45 Hz). Confusion matrices of phase classification and power classification are plotted in F = 6.28, p = 0.001, ηp2 = 0.310) and Inclusion  = 16.34, p = 0.001, ηp2 = 0.539). The 2-way interactions between Frequency band and Inclusion  = 6.28, p = 0.001, ηp2 = 0.310) and between Stimulus-type and Frequency band  = 5.42, p < 0.001, ηp2 = 0.279) were significant as well as the 3-way Stimulus type × Frequency band × Inclusion interaction  = 5.42, p < 0.001, ηp2 = 0.279). To further examine how each frequency band contributes to classification for each stimulus type, paired t tests with adjusted FDR correction were performed on each frequency band and each stimulus type. The theta band contributes to the decoding of all stimulus types  = 8.16, p < 0.001, d = 2.11; for α sounds, t(14) = 3.68, p = 0.010, d = 0.95; for γ sounds, t(14) = 3.16, p = 0.021, d = 0.82). The beta band deteriorated decoding of γ sounds (t(14) = −4.66, p = 0.002, d = 1.20). Crucially, the alpha band did not contribute significantly to decoding any stimuli. Before adjusted FDR correction, the gamma band shows a contribution to decoding γ sounds (t(14) = 2.07, p = 0.057, d = 0.53). After removing 1 subject who showed abnormal decoding performance, we found that the gamma band significantly contributes to decoding γ sounds after FDR correction (t(13) = 3.35, p = 0.017, d = 0.90).Next, to explore how each frequency band might contribute to phase-based classification of different stimulus types, classification was conducted using different combinations of frequency bands . We then compared the classification performance that was obtained with or without a particular frequency band included in the analysis. For example, to quantify the theta band contribution, we obtained 2 values by either averaging D′ values across frequency band combinations that included the theta frequency band, or without the theta frequency band. The contributions of each frequency band to different stimuli are plotted in θ sounds is significantly larger than that for α sounds (t(14) = 3.06, p = 0.027, d = 0.79) and γ sounds (t(14) = 4.04, p = 0.006, d = 1.04) after Bonferroni correction. In the gamma band, classification performance for γ sounds is significantly larger than for θ sounds (t(14) = 2.74, p = 0.048, d = 0.71) and α sounds (t(14) = 4.79, p < 0.001, d = 1.24) after Bonferroni correction.Finally, because we found that the theta and gamma bands provided the main contributions to classification, we examined how classification performance in the theta band and gamma band progress temporally by using each time point of a phase series to classify a stimulus type. Classification was conducted in the theta band and the gamma band separately by combining the MEG channels selected from 500 ms before the onset of the stimuli to 2,000 ms after. We used a cluster-based permutation test to quantify significance of classification performance see  and founγ sounds; by averaging time points from 300 to 1,900 ms, we see significantly higher classification performance in the gamma band for γ sounds than for θ and α sounds. This argues for a higher degree of specificity for gamma tracking.The significant classification performance in the theta band after the onset of stimuli for all stimulus types demonstrates that the theta band not only entrains to sounds with corresponding modulation rates but also provides critical information for classifying stimuli of all modulation rates. The gamma band showed significant classification performance for To summarize the classification results: phase series in the theta band temporally track acoustic dynamics across all modulation rates (used in our study), which suggests that the theta band is not only entrained by modulation rates with corresponding frequency range but also chunks sounds with modulation rates outside of the theta band range into acoustic segments at a timescale corresponding to the theta period range. The gamma band specifically locks to modulation rates with a timescale corresponding to gamma band, approximately 30 ms. The contribution of the alpha band must be seen as functionally separate from the other bands.If, broadly speaking, the (paired) activity of the theta and gamma bands is associated with the construction of perceptual objects in audition, contrary to the alpha band, it stands to reason that the localization of the theta and gamma neural activity should be associated. The supporting information see  providesd′ and ITC was significant in the theta band for 3 stimuli  = 8.50, p < 0.001, d = 2.19; for α sounds, r = 0.378, t(14) = 3.50, p = 0.014, d = 0.90; for γ sounds, r = 0.417, t(14) = 3.64, p = 0.014, d = 0.94). The positive correlation between d′ and evoked power was significant in the theta band for θ sounds  = 8.20, p < 0.001, d = 2.12). Analysis of the correlation between d′ and induced power response showed a negative correlation. A significant negative correlation was found in the alpha band for α sounds  = −3.01, p = 0.049, d = −0.78) and in the gamma band for γ sounds  = −3.22, p = 0.048, d = 0.83). Adjusted FDR correction was applied to all tests.Connecting back to the behavioral data , we testThe ITC in the theta band showed significant correlation with behavioral performance on recognizing all 3 sounds. These results echo the classification results and demonstrate that the phase series in the theta band provides critical information for auditory processing.In this MEG-based neurophysiological experiment, we investigate temporal coding at different scales by exploring the entrainment of auditory cortical oscillations to sounds with different modulation rates. Because healthy listeners (appear to) perceive sounds that contain modulation rates over various temporal scales in a manner that reflects a continuous MTF with a low-pass filter shape ,72, the Contrary to this hypothesis, we find that oscillations in the (slower) theta and (faster) gamma bands reliably track acoustic dynamics—but not in the (intermediate) alpha and beta bands. Subsequent analyses showed that the information carried in the neural theta band contributes to the decoding of all modulation rates used in this study, whereas the gamma band mainly contributes to decoding only gamma-modulated sounds. Moreover, intertrial coherence in the theta band correlates with identification performance across all stimuli, underscoring that there is a clear perceptual consequence of the entrained oscillatory activity.Our results are consistent with previous work showing entrainment of auditory cortical activity to low acoustic modulation rates ,57,73–81γ sounds—indicates that the auditory system can track acoustic dynamics over short timescales, approximately 30 ms. This observation is consistent with studies using amplitude modulation created by binaural beats; in that work, strong entrainment both in the theta and gamma bands is found—but, again, not in the alpha or beta bands [The neural gamma band, in addition to the delta and theta bands, also reliably codes temporal information. The finding that the neural gamma band is entrained by sounds with a corresponding temporal modulation rate—and that this alignment contributes to the classification of ta bands . Recordita bands ,84. The ta bands . These sThe classification results we report show that the phase information of theta band oscillations contributes to decoding sounds with modulation rates not only at the theta band timescale but also at the alpha and gamma scales. One possible explanation is that theta band oscillations (i) track acoustic dynamics at that specific temporal scale and (ii) at the same time actively chunk  sounds with faster modulation rates, so that acoustic properties over larger scales can be further extracted . The gamThe classification results also reveal data patterns that have not been shown in previous findings on the MTF. As the MTF shows decreased neural responses with increasing modulation rate, it is plausible to conjecture that temporal coding for acoustic dynamics would also show such a pattern. However, as observed in the classification analysis, the temporal coding capability does not correspond to the magnitude of the MTF—large ITC values for the alpha band do not indicate high temporal coding capability. Some previous findings, though, do show a tendency for a rebound of neural activity in the gamma band ,41,44, aThe absence or marked reduction of tracking acoustic dynamics in the alpha band suggests that neural activity reflected in the alpha band may play a different role in audition. In the auditory system, the neural computations reflected in the alpha band signal may be more explicitly involved in auditory attention, working memory, listening effort, or functional inhibition ,36–39,86The finding that, like alpha band activity, the beta band also does not track acoustic dynamics may reflect that neural oscillations on that scale are reflective of different operations as well. Beta band oscillations have been argued to play a role in predictive coding ,94; the θ sounds and γ sounds more easily simply because the modulation rates of these 2 sounds are located at the perceptual extremes in this experimental design. We acknowledge that this behavioral task is suboptimal—and primarily employed to ensure attention during neurophysiological recording—so we scrupulously refrain from overinterpreting these data, beyond pointing out that the pattern is consistent with our hypothesis. Notwithstanding this potential concern, results from a recent psychophysical study dovetail with the view that the auditory system works concurrently on a short timescale (about 30 ms) to extract fine-grained acoustic temporal detail while processing more global acoustic patterns on a longer timescale (>200 ms) [Our finding of entrainment, and specifically concurrent parallel processing at different scales of the theta and gamma bands, converges with the 2 perceptual time constants often found in behavioral studies . Experim>200 ms) .Importantly, our results, based on nonspeech stimuli, suggest that such dual-scale entrainment is not speech specific but may rather reflect an intrinsic auditory processing property. The auditory cortex tunes to both theta frequency and gamma frequency acoustic dynamics . The alpMounting evidence shows that human perceptual systems employ a discrete process in which continuous signal information is broken up into segments ,30,97–99The study was approved by the New York University Institutional Review Board (IRB# 10–7277) and conducted in conformity with the 45 Code of Federal Regulations (CFR) part 46 and the principles of the Belmont Report.Sixteen right-handed volunteers  participated in this experiment. All participants provided informed written consent and received monetary compensation for their participation. Handedness was determined using the Edinburgh Handedness Inventory . All parWe created 3 stimulus types following the methods used in Boemio et al. (2005) and Luo and Poeppel (2012). Each stimulus was 2 s long and generated by concatenating narrow-band frequency-modulated segments. The mean starting frequency of each segment was randomly drawn from 2 frequencies, 1,000 Hz and 1,500 Hz. If the mean starting frequency is 1,000 Hz, the frequency-modulated segment could sweep up to 1,500 Hz. If the mean starting frequency is 1,500 Hz, the frequency-modulated segment could sweep down to 1,000 Hz. The bandwidth of segments was 100 Hz . We generated each segment by adding up 100 frequency-modulated sinusoids with randomized amplitude and phase. To create a segment that sweeps down, the starting frequency of 100 sinusoid is randomly distributed between 1,450 Hz and 1,550 Hz and the end frequency is distributed between 950 Hz and 1,050 Hz. To create a segment that sweeps up, the starting frequency of 100 sinusoid is randomly distributed between 950 Hz and 1,050 Hz and the end frequency is distributed between 1,450 Hz and 1,550 Hz.θ) sound, the stimulus type with mean segment duration of 100 ms as an alpha (α) sound, and the stimulus type with mean segment duration of 27 ms as a gamma (γ) sound. The cochleograms of the 3 stimuli were created using a Gammatone filterbank with 64 banks to decompose the stimuli from 50 to 22,050 Hz [The duration of the segments for each of the 3 stimulus types was drawn from a Gaussian distribution with means of 190 ms, 100 ms, and 27 ms, with standard deviations of 30 ms, 15 ms, and 3 ms, respectively. The distribution of the segment durations of the stimuli aligned with the range of periods typical of theta (4–7 Hz), alpha/low beta (8–15 Hz), and low gamma (30–45 Hz) band neural oscillations. We refer to the stimulus type with mean segment duration of 190 ms as a theta  noise-masked stimuli. In total, 540 trials  were presented. The order of all stimuli was pseudorandomized for each participant. After each stimulus was presented, participants were required to push 1 of 3 buttons to indicate the type of stimulus. Between 1 and 2 s after participants responded, the next stimulus was presented, so that all stimuli were presented at random onset points. Participants were required to keep their eyes open and to focus on a white fixation cross in the center of a black screen.We generated white noise segments of 4 s using the random number generator, the function “randn,” in Matlab R2014a . Then, we embedded the 3 types of clean stimuli into white noise to create noise-masked stimuli at 5 levels of SNR: −9, −13, −17, −21, and −25 dB. The onset of white noise preceded the onset of the embedded clean stimulus for a random interval uniformly distributed from 1 s to 1.5 s. Thirty stimuli for each SNR level and each stimulus type were created using individually generated noise. As only 1 sample of each stimulus type was generated, the All stimuli were normalized to about 65 dB SPL and delivered through plastic air tubes connected to foam ear pieces .MEG signals were measured with participants in a supine position and in a magnetically shielded room using a 157-channel whole-head axial gradiometer system . A sampling rate of 1,000 Hz was used with an online 1–200 Hz analog band-pass filter and a notch filter centered around 60 Hz. After the main experiment, participants were presented with 1-kHz tone beeps of 50 ms duration as a localizer to determine their M100 evoked responses, which is a canonical auditory response . Ten chaBehavioral data analysis was conducted in MATLAB using the Palamedes toolbox 1.50 . For eacMEG data analysis was conducted in MATLAB using the Fieldtrip toolbox 20140619  and waveTo extract time-frequency information, single-trial data for each condition in each MEG channel were transformed using functions of the Morlet wavelets embedded in the Fieldtrip toolbox, with a frequency ranging from 1 to 50 Hz in steps of 1 Hz. To balance spectral and temporal resolution of the time-frequency transformation, from 1 to 20 Hz, the window length increased linearly from 1.5 circles to 7 circles and was kept constant at 7 circles above 20 Hz. Phase and power responses  were extracted from the wavelet transform output at each time-frequency point.z-score of ITC was computed using the percentile of the original ITC in the distribution.The ITC, a measure of consistency of phase-locked neural activity entrained by stimuli across trials, was calculated for each time-frequency point (details as in ). ITC inInduced power was normalized by dividing the mean power value in the baseline range (−0.6 to −0.1 s) and taking logarithms with base 10 and then was converted into values with the unit of decibel by multiplying by 10. The evoked power response was computed by applying the time-frequency transform on averaged temporal responses across all trials. The baseline correction was the same as that used in computing the induced power.The ITC and power data were averaged from 0.3 s to 1.8 s poststimulus onset to minimize the effects of stimulus-evoked onsets and offsets and within 4 frequency bands: theta (4–7 Hz), alpha (8–12 Hz), beta (13–30 Hz), and gamma (31–45 Hz).d′ and either ITC or power across the 5 SNRs, and then a 1-sample t test was performed for each frequency band and each stimulus type to determine whether the correlation is significant. As ITC is not normally distributed, the rationalized arcsine transform was applied before calculation of correlation coefficients [To examine whether phase and power in different frequency bands can explain behavioral performance, correlations between behavioral performance and neural measurements were tested by calculating correlation coefficients between ficients .All calculations were first conducted in each MEG channel and then averaged across selected auditory channels. Statistical analyses of ITC and power were conducted separately for the 3 clean stimuli and the 15 masked stimuli using rmANOVA. When multiple comparisons were performed, to control familywise error rate and, at the same time, not to cause a high rate of false negatives, the Bonferroni correction was used when there were less than 10 comparisons performed, and an adjusted FDR was used when there were more than 10 comparisons performed ,68.The stimuli in this study were created by concatenating frequency sweep segments of different durations, which may create sharp acoustic edges at the boundary between 2 adjacent segments. These acoustic edges indicate boundaries of frequency sweep segments and represent (one aspect of) the temporal structure of the stimuli, which correlates with modulation rates. By computing mutual information between temporal patterns of these acoustic edges and phase series of MEG signals, we can investigate in which frequency band the neural phase pattern best correlates with the temporal structure of stimuli. The results could tell us whether a frequency band is more or less involved in processing certain stimuli.θ sound having the fewest drops and the γ sound having the most drops.To quantify the acoustic edges and extract the temporal structure of the stimuli, inspired by the concept of cochlear-scaled entropy , we creaθ, α, and γ sounds [θ sounds and the 3 phase series evoked, respectively, by θ, α, and γ sounds, we used the phase series evoked by α and γ sounds as control conditions and examined whether MI between the cochlear-scaled correlation of θ sounds and the phase series evoked by θ sounds is significant. The mutual information value of each frequency was calculated for each subject and for each channel across trials before averaging.To quantify shared information between the cochlear-scaled correlation and phase series of MEG signals, we used the framework of mutual information ,113. Mutγ sounds ,80,116. The cochlear-scaled correlation we compute is simply the values at each time point corresponding to the time point of phase. For each frequency of the MEG response, the phase distribution was composed of 6 equally spaced bins: 0 to pi/3, pi/3 to pi * 2/3, pi * 2/3 to pi, pi to pi * 4/3, pi * 4/3 to pi * 5/3, and pi * 5/3 to pi * 2. By choosing 6 bins for phase information, we ensured that there was enough temporal resolution to capture acoustic dynamics, because (at least) greater than 2 times the temporal resolution than the frequency focused on is needed to quantify information at the frequency. The cochlear-scaled correlation was grouped using 8 bins equally spaced from the minimum value to the maximum value. Eight bins were chosen because we wanted to have enough discrete precision to capture changes in acoustic properties while making sure that each bin has sufficient counts for mutual information analysis, because the greater number of bins would lead to zero counts in certain bins.The estimation of mutual information is subject to bias caused by finite sampling of the probability distributions because limited data were supplied in the present study . Therefore, a quadratic extrapolation embedded in the Information Breakdown Toolbox was applied to correct bias. MI is computed on various subsets of the trials of the dataset of each condition. A quadratic function is then fit to these data points, and the actual mutual information is taken to be the zero-crossing value. This new value reflects the estimated mutual information for an infinite number of trials and greatly reduces the finite sampling bias ,118.2 norm of the linear distance was used for power classification. A trial was given 1 template’s label if the distance between this trial and the template was the smallest among 3 templates.A single-trial classification analysis of stimulus type was carried out on the clean stimulus condition to examine how the auditory system encodes information at different timescales. The procedure was described in detail in Ng et al. (2013), and similar methods were also used in Luo and Poeppel (2012), Herrmann et al. (2013), and Cogan et al. (2011). For each stimulus type, 1 trial was left out, and then a template was created by averaging across the remaining trials for this type of stimulus (the circular mean is used for phase average). Three templates were created, and the distance between each template and the left-out trial from 1 of the 3 stimulus types was computed. The circular distance was applied for phase classification by taking the circular mean over time and frequency; the ld′ was calculated based on hit rates and false alarm rates and averaged across all auditory channels. Instead of d′, D′ was used to differentiate d′ computed in the classification analysis from d′ in behavioral results. An index of classification efficiency using phase and power response of difference frequency band was indicated by the mean of D′ over 3 stimulus types, which was compared to the total d′ of the identification task, which indicates participants’ sensitivity in the behavioral study [A confusion matrix of classification was constructed by carrying out classification for each trial of each stimulus type on each auditory channel. Then, classification performance was measured using the same method used in the behavioral data analysis: correctly labeling the target stimulus was counted as a “hit” while labeling the other 2 stimuli as the target stimulus was counted as “false alarm;” al study .θ sound has a high log likelihood in the distribution estimated by 24 trials from α sound but lower log likelihoods in the other 2 distributions, we classified this left-out trial from θ sound as from an α sound.We carried out classification analysis using only the theta and the gamma bands on each time point to examine how classification performance progresses temporally in 2 frequency bands. We assumed that, on each time point, phase angles across trials can be summarized using a von Mises distribution—the circular analogue of the normal distribution—with its mean approximated by the group mean of phase angles across trials and its kappa value, an index for variance of von Mises distribution, estimated by computing variances of phase angles across trials . For eacA confusion matrix of classification was constructed by carrying out classification on each time point in each frequency band for each trial of each stimulus type. Then, classification performance was converted to D′ using the procedure described above in Single-trial classification.t tests to determine whether D′ on each time point is larger than the baseline line, D′ = 0. We set the threshold of significance as 0.05 and computed cluster-level t values of each cluster comprising time points above the threshold. The cluster with the largest cluster-level t value was picked for creating a distribution. This procedure was repeated 1,000 times and a distribution over cluster-level t values was formed. We set the 95th percentile of the distribution over cluster-level t values as the threshold. Then, on the classification results from the original data, we conducted a 1-tailed 1-sample t test in each frequency band for each sound and set the threshold as 0.05. The cluster-level t values of clusters comprising time points with significant classification performance were computed and the clusters with cluster-level t values larger than the threshold determined from the distribution created by permutation were considered as significant clusters. This cluster-based permutation test was conducted in each frequency band for each sound.A cluster-based permutation test was conducted on the classification results . For eachttp://dx.doi.org/10.5061/dryad.f357r [Data are deposited in the Dryad repository: ad.f357r .S1 Text(DOCX)Click here for additional data file.S1 Sound(WAV)Click here for additional data file.S2 Sound(WAV)Click here for additional data file.S3 Sound(WAV)Click here for additional data file.


The results show that the most abundant OCP residues in the breast milk was ΣDDT with the geometric mean ± standard deviation of 9.81 ± 7.52 ng−1 lipid−1 followed by ΣHCH (0.539 ± 0.557 ng−1·lipid−1). In the principal component analysis, cis-chlordane (cis-CHL) and γ-HCH were found to be related to participants who received medical treatment for infertility, and 4,4′-DDT was associated with those who received gynecological surgery. The logistic regression showed that the odds ratio (OR) of log γ-hexachlorocyclohexane (γ-HCH) was higher for mothers who had received medical treatment for infertility than for the normal group  after adjustments for age, pre-pregnant BMI, annual income, population , birth year, and parity. Cow milk and beef consumption as well as menstruation characteristics such as average menstrual period (>5 days), shortest menstrual period (<3 days), and women who had taken hormonal drugs were significantly associated to several OCP residues in the breast milk. In addition, ΣHCH including β-HCH and γ-HCH was correlated with annual family income and gravidity as well as cow milk and beef consumptions. Overall, γ-HCH exhibited a probable association with the infertility diseases of Taiwanese women, and dietary habit might play an important role in the female Taiwanese exposure to OCPs.Only few studies have focused on organochlorine pesticides (OCPs) in breast milk and the related health risks for women in Taiwan. Our goal is to examine breast milk OCPs and their associations with female reproductive function  as well as their correlation with sociodemographic parameters , annual incomes, population, birth year, and parity) and dietary habit. The breast milk samples were collected in southern Taiwan ( Organochlorine pesticides (OCPs) are a class of persistent organic pollutants (POPs) that accumulate in the environment and can be distributed through runoffs into surface water or groundwater . OCPs wip-p′-dichlorodiphenyldichloroethylene (DDE) cause endocrine disruption by increasing the free thyroxine (T4) and total triiodothyronine (T3) levels and found DDE to be inversely associated with thyroid-stimulating hormone (TSH). Reproductive toxicity studies linking OCPs to female infertility and gynecological issues date back to as early as the 1980s [−1 b.w.) for 7 days showed a reduction in seminal vesicle weight, serum testosterone, and dehydroepiandrosterone levels [−1) and lindane (0.8 mg kg−1) exhibited reduced ovulation rates [−1 were significantly correlated to low pregnancy rates in German women [n = 1722). However, an opposite trend was observed in a Brazilian study that showed that serum DDE from spontaneously pregnant women (fertile group achieving pregnancy in a period no longer than 12 months continuously) was significantly lower in magnitude than those receiving medical treatments for infertility [OCPs negatively affect human health and have been reported to cause endocrine disruption, reproductive toxicities, neurological disorders, immunotoxicity, and oncogenesis . Meeker,e levels  while maon rates . Althougon rates . An epidan women . On the an women  indicateertility . Infant ertility , reproduHuman breast milk is a convenient specimen that can be used to examine OCP residues in human tissues because it is a non-invasive type of sample . The OCPThe study protocol was reviewed and approved by the Human Ethical Committees of Pingtung Christian Hospital (PCH) in 2013. The study participants were pregnant women without clinical complications recruited from the PCH, Southern Taiwan, from December 2013 to November 2016. The initial selection comprised 143 randomly selected pregnant women ranging in age from 19 to 40 years old. Sixty-eight women were selected based on compliance with the following five criteria: completeness of the questionnaire, native- and nonnative-born populations with minimum residence times of 10 and ≥1 years in Southern Taiwan, respectively (to avoid the inclusion of participants who resided in POP emission areas), no history of PCB poisoning, sufficient breast milk supply (>60 mL), and willingness to strictly follow the protocol to prevent contamination. All participants answered the detailed questionnaires to provide the information for demographic and sociodemographic characteristics, dietary habit, and health or medicine history. The demographic and sociodemographic characteristics were maternal age, pre-pregnant and perinatal body mass index (BMI), parity, population, duration of breastfeeding, educational level, annual family income, and primiparity or multiparity. The dietary habit included the consumptions of cow milk, cheese, egg, beef, pork, and chicken. The self-reported items concerning medicine history such as “Infertility medical treatment” and “Gynecological surgery” were also provided . The his13C12-4,4′-DDT and pentachloronitrobenzene, purchased from Cambridge Isotope Laboratories , were added into a solution containing 2 mL of breast milk, 2 mL of glacial acetic acid, and 2 mL of methanol. The mixture was vortexed and sonicated in an ultrasonic bath for 30 min, and this mixture was moved to a vacuum manifold  using a 6 cc/5 mg Sep-Pak Vac C18 cartridge , a 360 mg Sep-Pak Plus NH2 cartridge (Waters), and a 3 cc/1 g Bond Elut PCB cartridge  for solid phase extraction. Twenty different OCPs  including 4,4′-dichloro-diphenyldichloroethane (DDD), 4,4′-DDE, 4,4′-DDT, α-hexachlorocyclohexane (HCH), β-HCH, γ-HCH, δ-HCH, cis-chlordane (CHL), trans-CHL, heptachlor, heptachlor epoxide, aldrin, endrin, endrin aldehyde, endrin ketone, dieldrin, decachlorobiphenyl, endosulfan I (a), endosulfan II (b), endosulfan sulfate, and methoxychlor were determined in the breast milk. For the lipid analysis, each breast milk sample was extracted twice using 200 mL acetone/n-hexane (2:1) for 8 min with stirring and filtration. After extraction, the extract was concentrated until dry, and the lipid content was determined using the gravimetric method. The final extracts were analyzed using high resolution gas chromatography equipped with mass spectrometry in the splitless mode  and a capillary column  separation in the electron impact (EI) mode. The temperature program of the GC oven increased linearly by 10°C·min−1 from 80 °C to 290 °C and was then maintained for 10 min at 290 °C. Two isotopic masses were measured for each mentioned component. Quantification was performed using the isotope dilution method with internal/external standard mixtures. The sample quality control and quality assurance (QA/QC) followed the Taiwan Environmental Protection Agency (EPA) standard method (NIEA T206.21C). The recovery rates of two isotopically labeled standards ranged from 97.4 to 103%. The range of method detection limit (MDL) values, defined as three times the signal-to-noise (S/N) ratio, were from 0.0155–0.0536 ng·g−1 ·lipid−1 for the twenty OCPs. In the present study, all of the milk samples were collected from participants who were within the normal duration of pregnancy (36 to 40 weeks), and the milk samples were collected within three weeks after giving birth. The milk samples were collected using chemical-free glass-bottles with Teflon seals and were then frozen in home refrigerators (0–4 °C). After 60–90 mL of breastmilk were collected, the glass bottles were immediately transferred to the laboratory at National Pingtung University of Science and Technology, and the samples were kept frozen at −20 °C prior to OCP analysis. OCP residues in breast milk were analyzed following the protocol from a previous report . The breU and Kruskal-Wallis H tests were used to examine the different groups. The OCP levels were logarithmically transformed to fulfill the normal distribution for statistical analysis. The correlations between the questionnaire parameters  and exposure levels were tested using principal component analysis (PCA) tests. The stepwise linear regression was used to test the correlation of dietary habit and menstrual characteristics against OCP residues in breast milk. Odds ratios (ORs) of mothers’ exposure to OCPs were tested against the parameters of demography or sociodemography, gynecological diseases, menstruation, and dietary habit, using a logistic regression with adjustment variables for pre-pregnant BMI, age, population, annual income, birth year, or parity. In this study, a result was deemed to exhibit statistical significance when it had a p-value of ≤0.05. All statistical analyses were performed using Statistical Product and Service Solutions (SPSS), version 12.0 The data for OCPs below MDLs were replaced with their corresponding half MDL (1/2 MDL) values for further statistical analysis. Nonparametric methods, including Mann-Whitney −2, and 2.21 ± 0.939, respectively. 39.7% of the investigated women were born before 1975. The sample of pregnant women comprised 23.5% primiparous and 77.5% multiparous women. For the population composition, 75% were native-born Taiwanese; 17.6% were native-born aborigines, and 7.4% were nonnative-born Taiwanese. 8.8% of the subjects had reached pre-senior high school levels of education, 39.7% had completed senior high school, 45.6% had attended a tertiary school, and 5.9% had completed graduate school. In addition, the annual income of the pregnant women was also included, with classifications of <$10,000 (14.7%), $10,000–$20,000 (32.4%), $20,000–$34,000 (36.8%), and >$34,000 (16.2%). For the duration of breastfeeding, 2.9% of the pregnant women breastfed their babies less than 2 months. Nine and eight subjects had received medical treatment for infertility and gynecological surgery, respectively. In addition, three participants had an overlap of treatments between infertility and gynecological surgery history. The frequency of the dietary habit and menstruation characteristics in the studying participants are also reported in −1·lipid−1 for aldrin, 0.839 ± 0.557 ng·g−1·lipid−1 for ΣHCH , 0.161 ± 0.284 ng·g−1·lipid−1 for ΣCHL (the sum of cis- and trans-CHLs), 0.161 ± 1.64 ng·g−1·lipid−1 for 4,4′-DDD, 8.07 ± 6.53 ng·g−1·lipid−1 for 4,4′-DDE, 0.360 ± 0.798 ng·g−1·lipid−1 for 4,4′-DDT, 9.81 ± 7.52 ng·g−1·lipid−1 for ΣDDT , 0.170 ± 0.500 ng·g−1·lipid−1 for dieldrin, 0.290 ± 0.776 ng·g−1·lipid−1 for Σendosulfan , 0.381 ± 0.701 ng·g−1·lipid−1 for Σendrin , 0.645 ± 0.995 ng·g−1·lipid−1 for Σheptachlor (the sum of heptachlor and heptachlor epoxide), and 0.0388 ± 0.145 ng·g−1·lipid−1 for methoxychlor. The highest OCP level was that of 4,4′-DDE, followed by the residue levels of Σheptachlor and ΣHCH in the breast milk of the Taiwanese subjects. The OCP levels of breast milk in this study , p,p′-DDE (228 ng·g−1·lipid−1), α-CHL (7.4 ng·g−1·lipid−1), heptachlor epoxide (4.0 ng·g−1·lipid−1), and heptachlor (2.3 ng·g−1·lipid−1) and the ban of OCP use since 1975 in Taiwan).is study  were lowH test was used to examine the significance of OCP levels with regards to pre-pregnant BMI, maternal age, population, parity, and annual income (data not shown). The older mothers (age > 31) had significantly higher cis-CHL levels in their breast milk than the younger ones (age ≤ 31) (p = 0.043). In addition, the levels of aldrin (p = 0.041), 4,4′-DDD (p = 0.07), endosufan II (p = 0.12), and heptachlor (p = 0.06) for mothers who had higher pre-pregnant BMI values were significantly lower than those for mothers who had lower pre-pregnant BMI values. Native-born aborigines had significantly higher Aldrin breast milk levels (p = 0.018) and cis-CHL (p = 0.035) than native-born Chinese mothers. The mothers with annual family income > $34,000 (U.S. dollars) showed significantly lower residual levels of α-HCH and β-HCH than those with incomes <$10,000. In Taiwan, the use of OCPs was banned in 1975, so adjusted variables were used to determine the relation of women’s age to the bioaccumulation of OCPs in their breast milk  had significant correlation to milk consumption while beef consumption was significantly correlated to five OCPs, which included positive correlations to Log endrin ketone , Log endosulfan sulfate , and Log cis-CHL  but negative correlations to Log γ-HCH  and Log endrin  as shown on p = 0.047) showed a significant association with native-born aborigines compared with those who are native-born and nonnative-born Taiwanese. However, the log concentration of α-HCH  or ΣHCH  exhibited a significant correlation with the mothers with annual family income ≤20,000 US dollars in comparison to the mothers with annual income >$20,000 U.S. dollar. In addition, compared with the multiparous mothers, ΣHCH  was also significantly associated with mothers under the primiparous group. We didn’t find any significant correlation of OCP residues in breast milk to women’s birth year (before or after 1975), age (over or under 31 years old), pre-pregnant BMI (higher or lower than 21.7 kg·m−2), and education level (higher or lower than senior high school) when the logistic regression models were examined with the adjustment of confounders (−1) and beef consumption (>50 g·week−1) showed significant values, where significant correlations were found between the log concentrations of β-HCH , ΣCHL , endosulfan I , endosulfan II , Σendosulfan , endrin , endrin ketone , Σendrin , and Σheptachlor  with cow milk consumption, while log concentrations of trans-CHL , ΣCHL , endosulfan II , endosulfan sulfate , Σendosulfan , and methoxychlor  in the breast milk were found to be significantly associated with beef consumption. The statistical analysis using stepwise linear regressions showed that Log endrin ketone  and endrin ketone  were observed to be significantly associated with women whose average menstrual period days was >5 days. Furthermore, log concentrations of trans-CHL  was also significantly associated with the shortest menstrual period days together with ΣCHL . Women who were menstruating fewer than 3 days had a higher risk related to the compounds mentioned. Lastly, significant associations were found in log concentrations of Σendosulfan , heptachlor epoxide (isomer B) , and Σheptachlor  with mothers who had taken or were taking hormonal drugs (p = 0.035), while no significantly different results between OCPs levels and having undergone gynecological surgery history (p > 0.05) were found.As shown in ciations . Log conal drugs . The Oddal drugs . Comparecis-CHL and γ-HCH in the breast milk were associated with women having received infertility medical treatment  with a varimax rotation was used to determine the correlations between OCPs in the breast milk samples and participants who had received infertility treatment in obstetric clinics or those who had undergone gynecological surgery at gynecological clinics. Two OCPs, reatment  while 4,p,p′-DDT, p,p′-DDE, and p,p′-DDD in 1998 were 4.3, 4.4, 3.6, 69.4, 169.4, and 6.8 ng·mL−1, respectively [−1·lipid−1 for p,p’-DDT), p,p’-DDE, and β-HCH, respectively, while the data from 2003 to 2005 from Zhao, et al. [−1·lipid−1 for p,p′-DDE, β-HCH, α-HCH, and γ-HCH, respectively. Afterwards, the data in 2006, 2008, and 2010 from Zhou, et al. [−1·lipid−1 for β-HCH, HCB, and 4,4′-DDD (dominant OCPs), respectively. Minh, et al. [p,p′-DDE, p,p′-DDT, β-HCH, and p,p′-DDD in the breast milk of Vietnamese women from 2000 to 2001 were 420–6300, 34–6900, 11–160, and 3–50 ng·g−1·lipid−1, respectively. Among the OCPs in breast milk, DDT is still a dominant species in China and Vietnam, while β-HCH and HCB are the most prominent ones for Chinese mothers [−1·lipid−1 for p,p′-DDT, β-HCH, p,p′-DDD, heptachlor epoxide, and p,p′-DDE, respectively [−1 in four cities  where HCH was dominant in the breast milk samples [For example, in northern Thailand, the concentrations of heptachlor, heptachlor epoxide, γ-HCH, ectively . In Chinectively  reported, et al.  were 152, et al.  were 67., et al.  indicate mothers . Breast ectively . In othe samples . Therefo samples  and John samples  showed t samples , and Nor samples  have exh samples  and in t samples ,38,39.trans-CHL, respectively, after examining the stepwise linear regression models with adjustment of their confounders. 31.3% linearity of beef consumption could be explained by the predictors of log endosulfan sulfate, Log cis-CHL, Log γ-HCH, Log endrin ketone, and Log endrin when the stepwise linear regression model was used. In the stepwise linear regression, dietary habits like cow milk and beef consumption also had significant correlations (positive or negative) to OCPs, indicating that consumption of these foods was a possible exposure pathway for OCPs (−1·f.w.−1) and cow’s milk (approximately 4.5 ng·g−1·lipid−1) [Certain OCPs, especially for HCH isomers, have significant associations with sociodemographic characteristics in the present study. In a Tunisian study , levels for OCPs . Comparefor OCPs . Some OCfor OCPs . Our reslipid−1)  which islipid−1) . In thislipid−1)  reportedcis-CHL and γ-HCH in women who had received infertility treatments. Several epidemiological studies have indicated negative correlations between semen quality  and γ-HCH in semen or serum samples from male adults [trans-nonachlor, DDE, DDT, and dieldrin did not appear to be significant. Additionally, a hospital-based case and control comparison study indicated that the maternal and cord blood levels of α, β, γ-HCH in the control group were significantly lower than those in the small-for-gestational-age (SGA) case group while there were no significant differences observed for DDE, DDT, DDD, and endosulfan [As shown in e adults ,46,47. Pe adults . Upson ee adults  indicatedosulfan . trans-nonachlor, and dieldrin in serum were significantly associated with the prevalence of prostate cancer. In an age-period-cohort analysis conducted by Ho, et al. [Overall, based on the above-mentioned studies, HCH isomers in human samples seem to be associated with female reproduction disruption. Many studies have also indicated that γ-HCH is the detected dominant OCP residue ,50,51. X, et al.  a steady, et al. . Airaksi, et al.  indicate, et al. , and an , et al. . In addi, et al. , reduced, et al. , endocri, et al. , allergi, et al. , immunot, et al. , and onc, et al. .n = 68) and small number of infertility cases (n = 9) as compared to the control (n = 59). Thus, this situation might not be adequate to explain the significantly higher γ-HCH breast milk levels in women receiving infertility treatments as compared to that of the normal women. Exposure to OCPs may delay conception and cause infertility [cis-CHL and 4,4′-DDT must be closely monitored due to their high potential risks associated with infertility and gynecological diseases. Aside from fertility studies, the association of OCPs to female reproductive-associated surgeries and technologies has also been investigated. Zhu, et al. [−1·lipid−1). Our results offer valuable information for encouraging future in-vitro, in-vivo, and epidemiological studies on associations between the body burden of γ-HCH and female infertility. In this study, the logistic regression exhibited high ORs of γ-HCH or lindane in mothers who received infertility treatment as compared to the normal group after adjusting for age, pre-pregnant BMI, annual income, and population . Our resertility . Previouertility . Consideertility ,46,65. Iertility , and γ-H, et al.  measuredMenstrual parameters, including average periods of menstrual cycle (≤26 and ≥30 days), average menstrual period days (>5 days), shortest menstrual period days (≤3 days), hormonal drug intake, and infertility in association with OCP residues in breast milk were investigated. Infertile women and those who had taken hormonal drugs had significantly high ORs of OCPs, while women with menstrual cycles of ≤3 days had significantly higher OCP ORs than those whose menstrual duration was greater. A low OR of endosulfan II was observed in women with irregular menstrual periods (≤26 and ≥30 days); however, there was no significant association observed. Currently, there is no epidemiological evidence associating OCPs with menstruation; however, there have been reports linking menstruation characteristics with other pollutants. In our previous studies ,69, highn = 68) and the fact that our participants might not have been willing to report that they had undergone gynecological surgery or had received treatment for infertility. Although several significances were found in the tests using a logistic regression and a PCA model, these statistical methods were possibly not the best choices for the examination of the associations of OCPs to health outcomes in the present study, which was not a case-control designed study. More detailed information is provided in the The limitation of this work is that it was a part of an on-going follow-up study to examine the health effects after mother-infant pairs were exposed to organochlorines. It was not easy to show significance in the statistical analysis due to the small sample size (−1 of body weight), also revealing a low risk to Taiwanese health (within safe levels). The levels of breast milk OCP may reflect the body burden in women of child-bearing ages and their effects on nursing infants and adults , and thear 1975 ) and breear 1975 ,72, or tear 1975 ,74 increcis-CHL and γ-HCH were associated with menstruation characteristics, hormonal drug intake, infertility treatment, cow milk consumption, and beef consumption. Accordingly, dietary habit is an important factor influencing the levels of OCPs in breast milk and the associated risks for women. Even after the long-term ban of OCPs use in Taiwan, the OCP residues in human breast milk samples were detectable. The most dominant OCP species was ΣDDT, followed by ΣHCH. Our results were significantly lower as compared to those observed in some developing and developed countries. Sociodemographic characteristics especially annual family income and gravidity were found to be correlated to several OCPs, particularly ΣHCH. In addition to these two sociodemographic characteristics, dietary habits such as consumptions of cow milk and beef were also associated with ΣHCH. Moreover, other OCPs such as