The transition from adolescence to adulthood is associated with brain remodeling in the final stages of developmental growth. It is also a period when a large proportion of this age group engages in binge alcohol drinking  and heavy alcohol drinking (binge drinking on ≥5 d in a month). Here we report on magnetic resonance imaging of developmental changes in the brain occurring during late adolescence and early adulthood (3.5–7.5 years of age) in a rhesus macaque model of alcohol self-administration. Monkeys were imaged prior to alcohol exposure, and following ∼6 and ∼12 months of daily (22 h/d) access to ethanol and water. The results revealed that the brain volume increases by 1 ml/1.87 years throughout the late adolescence and early adulthood in controls. Heavy alcohol drinking reduced the rate of brain growth by 0.25 ml/year per 1 g/kg daily ethanol. Cortical volume increased throughout this period with no significant effect of alcohol drinking on the cortical growth rate. In subcortical regions, age-dependent increases in the volumes of globus pallidus, thalamus, brainstem, and cerebellum were observed. Heavy drinking attenuated the growth rate of the thalamus. Thus, developmental brain volume changes in the span of late adolescence to young adulthood in macaques is altered by excessive alcohol, an insult that may be linked to the continuation of heavy drinking throughout later adult life. Chronic alcohol self-intoxication reduced the growth rate of brain, cerebral white matter, and subcortical thalamus. Thus, daily alcohol drinking during the critical transition to adulthood significantly impacts critical areas of sensory motor integration, concomitant with a decrease in cortical white matter, documented in the primate brain neural circuitry implicated in the propagation of alcohol use disorder.Alcohol abuse during late adolescence and early adulthood is a risk factor for the development of alcohol dependence. This longitudinal study used a macaque model of alcohol self-administration and In vivo magnetic resonance imaging (MRI) studies in humans and other species have confirmed that the brain volume (VB) continues to increase throughout childhood and adolescence , which is designed to quantify the longitudinal effects of low and heavy alcohol use in children throughout adolescence on the development of cortical regions and the white matter. Importantly, this study includes scanning subjects before any alcohol use .n = 58) and female (n = 13) rhesus monkeys  were obtained from the Oregon National Primate Research Center (ONPRC) breeding colony. All monkeys except cohort 4 were enrolled in the study at 3.5–5.5 years of age and 3–6 kg in body weight. All animals were housed indoors in rooms with controlled temperature (20–22°C), humidity (65%), and an 11 h light cycle with lights on at 7:00 A.M. Each subject was housed in a metal cage (0.8 × 0.8 × 0.9 m) and fed a diet of nutritionally complete 1 g of banana-flavored pellets (TestDiet) and fresh fruit. Food and fluid availability was dependent on experimental phase, as described below. All monkeys were weighed weekly, and ethanol intake based on body weight (in grams per kilogram) was calculated from the contemporary weights. All procedures were conducted according to the Guide for the Care and Use of Laboratory Animals  ethanol . The indN = 61, including only adolescent cohorts; i.e., cohort 4 excluded). Subsequently, an additional 171 ± 16 self-administration sessions were allowed (∼12 months of open access). The study timeline for each cohort is shown in When induction to ethanol drinking was completed, all animals were allowed daily “open access” to water and ethanol  for 22 h/d, 7 d/week . During Before MRI and ethanol self-administration sessions, all animals were trained to comply with veinipuncture procedure without the use of anesthesia. Initially, subjects were trained to present their leg through an opening in the front wall of the housing cage. They then were trained to comply with blood sampling to be reinforced with raisins or trail mix. Blood samples were collected from the saphenous vein 30, 60, and 90 min after the start of the induction sessions and 7 h after the start of the 22 h drinking sessions in 4–5 d intervals. The blood samples were collected throughout the 3 months of ethanol induction and period of open access to ethanol. Ethanol content was assessed by gas chromatography .1-weighted magnetization-prepared rapid acquisition gradient echo (MP-RAGE) with one of the four imaging protocols described in 1), after 6 months of self-administration (MRI2), and after 12 months of self-administration (MRI3). Within each cohort, image acquisition settings were kept constant, except for cohorts 6a, 7a, and 7b, in which the MRI system was upgraded from a Trio to a Tim Trio between the MRI1 and MRI2 time points, and different MRI protocols were used for data acquisition in the cohorts. Between cohorts, experiments took advantage of upgrades in radiofrequency coil or scanner capabilities as they became available.Before an imaging session, each animal was anesthetized with ketamine  in the housing environment. The animal was transferred to the ONPRC MRI Core Facility, intubated and maintained anesthetized with 1–1.5% isoflurane throughout imaging procedures (≤2 h). The images were acquired using a 3 T Siemens Magnetom MRI system. For all subjects in this study, the MRI protocol included an acquisition of T1 to MRI3. At the beginning, the INIA19 template, which includes a T1-weighted head image, brain mask, and NeuroMap labels, was used a reference . Based on the registration results, the label map of the INIA19 template was transformed to the space of each MRI1 image. With the same method, the label maps of brain images in MRI2 and MRI3 were generated based on the resulting transformation parameters. Subsequent to the analysis of brain volume changes, a secondary analysis was performed to determine whether individual brain regions are differentially susceptible to age or ethanol exposure. Accordingly, we explored effect of ethanol on age-related changes on a finer scale by parcellating the brain volume into the following 10 well resolved regions of interest (ROIs): WM, cortex, putamen, caudate nuclei, globus pallidus, thalamus, amygdala, hippocampus, brainstem, and cerebellum, illustrated in eference . All coriY,j is VB, white matter volume (VWM) or volume of an ROI, as follows:Imaging data for all subjects collected longitudinally across three time points were analyzed using a linear mixed model (LMM). A series of LMMs were used in this study to estimate the effects of age and chronic ethanol drinking on volumetric characteristics of the primate brain where iY,j ∼ β0 + β1agei,j + jbsubject + εi,jLMM 1: iY,j ∼ β0 + β1agei,j+ β2intakei,j + β3agei,j × intakei,j + jbsubject + εi,jLMM 2: iY,j ∼ β0 + β1agei,j + β2groupi,j + β3agei,j × groupi,j + bjsubject + εi,jLMM 3.1: iY,j ∼ β0 + β1agei,j + β2groupi,j + β3sexi,j + β4agei,j × groupi,j + β5agei,j × sexi,j + β6groupi,j × sexi,j + β7agei,j × groupi,j × sexi,j + jbsubject + εi,jLMM 3.2 B of CTR animals using LMM 1, which incorporates a fixed effect of age (β1) and a random intercept (jb). Next, we explored whether the age effect on iY,j depends on ethanol intake using LMM 2 with fixed effects of age and average ethanol intake (β2), as well as an age-by-intake interaction (β3), and a random intercept.First, we estimated age-related change in the Vn = 19), and heavy and very heavy drinkers were grouped as HDs (n = 26). This parallels previous work in humans  was considered significant. The significant fixed effects and interactions found in linear mixed model analyses were followed by post hoc t tests in which p values were adjusted for the number of comparisons, and differences of p < 0.05 were considered to be significant.Subjects were categorized as low, binge, heavy, and very heavy drinkers based on the ethanol intake parameters of each individual during the open access period, as described in previous studies . Brieflyn humans  and in nn humans . The thi1) at ages ranging from 3.9 to 5.9 years and reached MRI3 at ages ranging from 5.6 to 7.5 years , 1.5–2.1]; the VB of CTR animals increases by 1 ml/1.87 years.Subjects were initially studied  averaged across drinking sessions before MRI2 and 105 ± 24.2 mg%  averaged across sessions between MRI2 and MRI3.After the induction period, 55 of the 71 animals were allowed to voluntarily self-administer ethanol during a 12 month period  and ethanol intake  significantly predicted VB, and these effects were interdependent, as demonstrated by a statistically significant age-by-intake interaction . Thus, brain growth occurred in all NHP subjects studied over this range; however, it was attenuated by a factor of 0.25 ml/year per daily gram per kilogram ethanol. i) and average ethanol intake of the subject across 12 months of open access .To explore whether chronic ethanol self-administration affects brain growth in nonhuman primates, we used LMM2 with age at MRI sessions 1-3, average ethanol intake, and the potential interaction between them as predictors of VB  = 141.9, p < 0.0001); however, the age-related VB was dependent on drinking group  = 5.5, p < 0.01). Multiple comparisons between groups , while a similar rate of increase of VB was observed in CTRs and NHDs . Importantly, the age-dependent changes in the VB significantly differ between two groups of NHD animals (late adolescent and adult) as depicted in F = 8.6, p < 0.01) on the age-related changes in VB. The brain continues to grow in younger NHD animals throughout the period from 4 to 7.5 years of age. In adult subjects, the growth stopped and VB declined by 0.27 ml/year. This differed from the adolescent NHD by 1.8 ml/year . Importantly, as indicated in F = 1.4, p = 0.24; effect of age: F = 68.7, p < 0.0001; effect of group: F = 1.4, p = 0.25; age × group interaction: F = 5.5, p < 0.01).An additional analysis was performed in which ethanol-drinking monkeys were categorized as NHDs and HDs. Drinking group  was used as a fixed factor in LMM 3.1 to compare age-related brain growth between subjects with different drinking status. n groups D show thn = 13) to examine the possibility that the effects of alcohol exposure on brain growth was sex dependent. The analysis using LMM 3.2 revealed a significant effect of sex on VB  = 91.4, p < 0.0001), but no significant interactions between sex and age  = 0.4, p = 0.5) and between sex and group  = 1, p = 0.35), or a sex × age × group interaction  = 1.7, p = 0.2). These findings correspond to previous reports demonstrating sex-dependent differences in the brain volume of humans and nonhuman primates . However, age-dependent changes in volumes were identified for the cerebellum, brainstem, globus pallidus, thalamus, and white matter. The cerebellum, brainstem, and globus pallidus exhibit a statistically significant effect of age, but no age × group interaction. As shown in Previous studies have demonstrated varying age-dependent changes in the volume of different brain structures  and haveAs shown in the WM growth was 0.6 ml/year, and it was slightly lower in NHDs by 0.07 ml/year compared with CTR animals. However, the rate of growth was robustly attenuated in HDs compared with CTR animals by 0.25 ml/year. To confirm that there were no group differences in the VWM at baseline (MRI1) before ethanol self-administration, we performed ANOVA. The analysis revealed no significant differences among three groups of monkeys  = 1.1, p = 0.35), where the average VWM at MRI1 was 19.9 ± 2 ml in CTR animals, 20.4 ± 1.7 ml in NHDs, and 20.9 ± 2.2 ml in HDs. 1) and the end of alcohol or water (control) self-administration (an ∼12 month period). In the CTR monkeys, VWM increased by 4.7 ± 0.4%. Similar to CTR animals, the 4.0 ± 0.5% increase in the VWM was observed in NHDs. In HDs, the increase in the VWM was significantly smaller (2.6 ± 0.3%) compared with CTR. One-way ANOVA revealed a significant effect of group  = 7.8, p < 0.001; post hoc analysis).In the CTR group, the estimated rate of VT) at baseline (MRI1) before ethanol self-administration using ANOVA. The analysis revealed no significant differences among the three groups of monkeys  = 0.3, p = 0.73), where the average VT at MRI1 was 1.7 ± 0.2 ml in CTR animals, 1.7 ± 0.15 ml in NHDs, and 1.7 ± 0.13 ml in HDs. The VT increased by 5 ± 0.7% between baseline (MRI1) and the end of self-administration in CTR animals and by 2.8 ± 0.6% in NHDs. In HDs, the 1.8 ± 0.6% increase in the VT was significantly smaller, as revealed as a significant effect of group in one-way ANOVA  = 5.5, p < 0.01; post hoc analysis).Thalamic growth also occurred in the NHP brain over this period B. In theRhesus macaques have been widely used as a translational model for investigating the neural substrates of human behavior and, particularly, alcohol use and abuse . The preAlthough the rate of brain volumetric growth decreases during development , the preThese neurodevelopmental underpinnings are thought to form the biological bases of robust behavioral and cognitive changes that occur concurrently and are accompanied by susceptibility to maladaptive behaviors in adolescents. Importantly, the age at onset of alcohol drinking is considered as one of the significant predictors of heavy alcohol drinking in adulthood . FurtherThere are numerous factors that could contribute to the observed impact of chronic alcohol drinking on brain growth. For example, cortical volume, which occupies the greatest volume fraction of the total brain in rhesus macaques , could aThe volume of subcortical structures also showed age-dependent growth in four of eight subcortical gray matter regions of interest included in the study . These findings partially correspond to a human cross-sectional pediatric study where the volumes of thalamus, brainstem, and cerebellum increase in a period from 4 to 18 years . The datIn summary, the NHP model of alcohol self-administration, in combination with longitudinal measures by MRI used in this study, highlights the rate of volume changes within the developing primate brain to isolate dose-dependent effects of chronic voluntary alcohol drinking in rhesus macaques. These effects are concentrated within cerebral white matter, and the thalamus is involved in critical control over sensory and limbic integration with behavioral choice and output. Thus, future research is needed to determine whether these volumetric changes might lead to altered functioning within the neural circuitry underlying excessive alcohol drinking.


To investigate the prevalence of cardiovascular disease (CVD) risk factors and assess the 10-year risk of CVD in non-menopausal and postmenopausal women with type 2 diabetes mellitus (T2DM).A total of 569 patients with T2DM at a Chinese tertiary hospital were investigated using the Framingham Risk Score (FRS). We evaluated the 10-year risk of CVD, clinical and menopause characteristics in all subjects.1c < 7%), blood pressure , and blood lipids . The 10-year risk of CVD was (1.6 ± 1.5%) and tended to increase along with age . For all subjects (n = 569), multiple linear regression analysis showed that menopause , low-density lipoprotein cholesterol (LDL-C) , fasting plasma glucose (FPG)  and waist-to-hip-ratio  were risk factors of 10-year risk of CVD, which may explain the variance of 14.3%. In the postmenopausal group (n = 397), LDL-C , FPG  and time since menopause  were found to be associated with CVD, which may explain the variance of 14.6%.Among the 569 diabetic patients, the incidence of smoking, dyslipidemia, hypertension, overweight or obesity, and nonalcoholic fatty liver disease (NAFLD) was 0.7, 36.2, 38.1 56.6 and 58.2%, respectively. The usage rate of hypoglycemic agents, antihypertensive agents, lipid modulators and antithrombotic drugs was 88.6, 78.3, 50.0 and 27.1%, respectively. However, only 1.2% of inpatients achieved the three target goals for the control of blood glucose (HbAThe incidence of dyslipidmia, hypertension, overweight or obesity and NAFLD is high. The level of control of blood glucose, blood pressure, and blood lipids was found to be extremely low and the treatment status was not ideal. Besides menopause, LDL-C, FPG and time since menopause were found to be independent risk factors for the 10-year risk of CVD. Therefore, it is necessary to focus on comprehensive control of multiple risk factors, such as plasma glucose, blood pressure and serum lipid. Cardiovascular disease (CVD) is a leading cause of mortality and morbidity worldwide . The preAs is well known, diabetes mellitus is a significant risk factor for developing CVD. The major pathological basis of CVD begins with endothelial damage or dysfunction , 8. A reThis cross-sectional survey was performed at a tertiary hospital in Changzhou, Jiangsu Province, China, using a convenient sample size of 600 admission patients with type 2 diabetes mellitus between January 2016 and January 2018. The inclusion criteria were female patients aged 18 years or above, who were admitted to the Department of Endocrinology, and had type 2 diabetes mellitus for at least 3 months and were able to communicate fluently and clearly. Exclusion criteria were patients with type 1 diabetes mellitus, dementia or a severe illness, such as cancer or other immune system diseases, serious accompanied diseases or complications, psychosis, coronary heart disease, arrhythmia, stroke and those who were pregnant or lactating. After excluding 31 subjects with missing clinical characteristics, 569 out of the 600 eligible participants completed the surveys, representing a 95.5% response rate.Patients who met the inclusion criteria and gave verbal informed consent were acquired to complete the surveys. The present study was approved by the Ethics Committee of the Hospital.1c, plasma glucose, C peptide levels, 4 items of blood lipid tests and apolipoprotein concentrations. Blood sampling was performed at a clinical testing center of our hospital. Two health care professionals who were trained as data collectors used uniform instructions to guarantee the quality of data collection. Two other data collectors obtained further information on age at menarche, menstrual days and cycle, menopause age, treatment regimens, hypoglycemia and complications, through face to face interviews. We classified the 569 patients into non-menopause (n = 172), postmenopause < 5 y (n = 231) and postmenopause ≥5 y (n = 166) based on whether they were menopausal or not and time since menopause.The patients were required to undergo a series of examinations, including demographic and clinical characteristics and a biochemical evaluation for the analysis. The information included age, diabetes course, family history, history of present illness, height, body weight, blood pressure, smoking, alcohol intake habits and current medications. Blood chemistry values assessed included HbAPatients were identified as dyslipidemic, if any one of the following indexes were met: total cholesterol (TC) level ≥ 240 mg/dL, low-density lipoprotein cholesterol (LDL-C) level ≥ 160 mg/dL, triglycerides (TG) level ≥ 88 mg/dL, high-density lipoprotein cholesterol (HDL-C) level ≤ 40 mg/dL or if the patients were taking lipid-regulating drugs .2; overweight, BMI 24–27.9 kg/m2; Obese, BMI ≥ 28 kg/m2 [A diagnosis of hypertension was made in the absence of antihypertensive drugs, when systolic blood pressure (SBP) ≥ 140 mmHg and/or diastolic blood pressure (DBP) ≥ 90 mmHg; a previous history of hypertension, currently using antihypertensive drugs . Weight 28 kg/m2 .A general check-up was performed by an internal medicine physician. Two independent radiologists interpreted the abdominal ultrasonography results of all patients at the time of the initial evaluation to determine the presence of NAFLD .1c < 7%, blood pressure < 130/80 mmHg and TC < 174 mg/dL, which are based on Guidelines for Diabetes Prevention and Treatment in China [The target goals of blood glucose, blood pressure and blood lipids were HbAin China .FRS was used to evaluate the 10-year risk of CVD . Based oP value of < 0.05 was considered to be statistically significant.IBM SPSS ver. 22.0  was used to perform the statistical analysis. All data are expressed as mean ± standard deviation or percentage, where applicable. T-test or one-way ANOVA (for continuous variables) and chi-squared test  were used to compare data between different groups. Non-parametric tests, including Mann-Whitney U test and Kruskal-Wallis H test, were used for data that did not show a normal distribution. Spearman correlation was used to examine the relationship between 10-year risk of CVD and associated factors, which including age, diabetes course, complications, plasma glucose, body mass index, blood lipid profile, reproductive factors and treatment regimen. A stepwise multiple linear regression model was performed. The 10-year risk of CVD was the dependent variable. Independent variables were those parameters that were statistically correlated to 10-year risk of CVD. For all statistical tests, a 2), waist-to-hip-ratio (0.904 ± 0.05), HbA1c (9.6 ± 2.7%), FPG (9.6 ± 2.9 mmol/L), 2hPG (13.7 ± 4.0 mmol/L), SBP (134.1 ± 18.0 mmHg), DBP (83.2 ± 10.7 mmHg), TC (181.4 ± 38.6 mg/dL), TG (92.6 ± 81.1 mg/dL), HDL-C (42.5 ± 11.6 mg/dL), LDL-C (92.6 ± 30.9 mg/dL), Apo A1 (1.1 ± 0.19 g/L) and Apo B (1.0 ± 0.30 g/L) (Table P <  0.001).The demographic and clinical characteristics of the study population and grouping are summarized in Table 1c < 7%), blood pressure (systolic blood pressure < 130 mmHg and diastolic blood pressure < 80 mmHg), and blood lipids  [Among the T2DM inpatients, the exposure rate of NAFLD, overweight or obesity, hypertension, dyslipidemia and smoking was 58.2, 56.6, 38.1, 36.2 and 0.7%, respectively. The prevalence of hypertension tended to increase with age (Table 4 mg/dL) .Table 2P <  0.001) (Table The Framingham Risk Score was 10.3 ± 4.5), and the 10-year risk of CVD was (1.6 ± 1.5%), and both indicator values increased along with the age , while the treatment regimens were independent variables, which were performed in a stepwise multiple linear regression model. The results are shown in Table β = 0.275, 0.212, 0.093, − 0.078, respectively, P < 0.05), which may explain the variance of 14.3%. Menopause, LDL-C, FPG and waist-to-hip-ratio were found to be independent risk factors for the 10-year risk of CVD.Among all subjects, the 10-year risk of CVD was a dependent variable, in addition to age, TC, SBP, smoking, diabetes course, complications, FPG, 2hPG, BMI, waist-to-hip-ratio, TG, LDL-C, Apo A1, Apo B, menopause age, time since menopause, total reproductive years and treatment regimens. LDL-C , FPG  and time since menopause  were found to be associated with CVD, which may explain the variance of 14.6% (Table In the postmenopausal group, 10-year risk of CVD was as dependent variable. Except for age, TC, SBP and smoking, the independent variables were diabetes course, complications, FPG, 2hPG, BMI, waist-to-hip-ratio, TG, LDL-C, Apo A6% Table .Table 5The findings of the present study indicate that the incidence of dyslipidemia, hypertension, overweight or obesity and NAFLD is high. All these indicators are considered to be conventional cardiovascular risk factors. The association between these factors and cardiovascular disease is well known , 24–26. We found that a higher risk of CVD was observed among diabetic patients who have experienced menopause, compared with non-menopausal women. The related factors are LDL-C and FPG levels. Two studies have shown that menopause has a marked effect on the circulation levels of lipids and lipoproteins, with an especially significant increase in LDL-C levels , 33. PreFurthermore, as the period of time since menopause increases, the CVD risk also increases. In a Chinese population study, compared to women who had been menopausal for less than 1 year, those with elapsed time since menopause of 2–3 years had higher coronary heart disease prevalence, and higher TG levels . Cho et This study has several limitations. First, although this is the first study to report that cardiovascular risk factors of menopausal women with type 2 diabetes mellitus, the study used a hospital-based cohort of a Chinese population, indicating that the study sample was from a single hospital. We cannot assume that our findings can be generalize to other groups. Second, the study population was hospitalized patients, which may have introduced a selection bias. In addition, there was also a memory bias in the study, especially when we asked some questions about reproductive factors, such as menstrual days, menstrual cycle, menopausal age, complications, and treatment regimen, subjects had to recall what had happened in the past, which is not the best method. Third, the lack of a non-diabetic age-matched control group was also a limitation of this study. Fourth, due to the observational nature of the study, the mechanisms proposed to explain the association between higher risk of CVD, menopausal status and FPG are merely speculative. Indeed, no tests of sex hormones have been performed. Finally, an analysis of the difference in autoantibody positivity between the non-menopause group and the menopause groups was not conducted, which is a shortcoming of this study.In conclusion, among women with type 2 diabetes mellitus in China, the prevalence of cardiovascular risk factors are high. Although there is overwhelming evidence to indicate that achieving adequate control of blood pressure and lipids can significantly delay or prevent the onset of CVD, successful accomplishment of recommended therapeutic goals is a huge challenge. In diabetic females, except for menopausal state and time since menopause being uncontrollable factors, LDL-C, FPG and waist-to-hip ratio were found to be controllable factors. The clinical management of diabetes needs change. In addition to monitoring plasma glucose, interventions to improve blood pressure, serum lipids and lifestyle are needed. These women are currently too young to have experienced CVD events, therefore, the continued follow-up of these women needs to be conducted.


This article presents experimental data for physical characteristics, fiber compositions, and tensile properties of non-flushable wipes, flushable wipes, and toilet papers. Samples included 42 flushable wipes, 16 non-flushable wipes, and 11 toilet papers that were collected from around the world by considering product diversity in their retail regions , manufacturers , and function . The data were generated in accordance with relevant standard methods of International Organization for Standardization (ISO). The data are provided here in full (not hosted by any public repository) in association with the research article: “Physical characteristics, fiber compositions, and tensile properties of nonwoven wipes and toilet papers in relevance to what is flushable” [ For clarity, we use an example case  x 336 (μm) x (1 cm/10000 μm) = 11.4 cm3,Sheet volume = 340 (cm2 x (10000 cm2 / 1 m2) = 176 g/m2,Basis weight = 6.0 g / 340 cm3 x (1 dm3 / 1000 cm3) / (6.0 g) x (1000 g /1 kg) = 1.9 dm3/kg.Specific volume = 11.4 cm1.21.3max) that is needed to break a sample, was measured and reported as the average of seven readings for each sample, 2- A tensile property, such as tensile strength, was computed by dividing the measured Fmax value with width of a specimen. For convenience, we use sample no.1 in max, and the elongation-at-break values for each of seven specimens of a sample. We reported the arithmetic average of seven readings as the measured properties as shown below for sample no.1 in By using the measured quantities and the equations below, we estimated tensile strength, tensile index, and breaking length of a sample as followsmax/width of a specimenTensile Strength = Fmax value for sample no. 1 (NF-SN-1) was reported as 27 N in The FTensile Index = Tensile Strength/Basis weight2 from 2) = 34.6 Nm/g for the sample (6th column of Basis weight of sample no. 1 (NF-SN-1) in Breaking Length = Tensile Index (Nm/g)/Gravitational Acceleration2) = 3529 m.Breaking Length of a sample is the length at which the sample will break due to its own weight. Accordingly, breaking length for sample no. 1 (NF-SN-1) in 22.1For thickness measurements, we used a light microscope,  at 100× magnification. This microscope can measure thicknesses as low as 50 μm at increments of 1 μm. 2.2Tensile properties of dry samples were measured according to standard method of ISO 12625 - Part 4: Tissue paper and tissue products – Determination of (dry) tensile strength, and stretch at break by using tensile apparatus operating with constant rate of elongation. We used a universal tensile testing machine  that was controlled by Trapezium X Materials Testing Software. The tensile instrument has two jaws with clamps that hold a strip of a sample in place during testing. The bottom jaw is fixed, while the upper jaw elongates a strip during a test run. For calibration of the instrument, we tested standard printing paper, toilet papers, and standard cardboard, for which tensile properties were available. Then, we prepared a single strip of a wipe (or TP) as 15 mm in width and >100 mm in length, and placed exactly 100 mm between jaws of the tensile machine. During testing, the upper jaw pulled a strip upwards, while the Trapezium X software controlled rates of loading, and separation of jaws. Force was applied at increments of 0.1 N, while the jaws were separated at a constant rate of 25 mm/min, and each strip broke between 15 and 30 seconds. Collectively, these steps confirmed constant rate of elongation for each strip as required by the ISO method. In accordance, we took 5 to 7 measurements for each specimen, and we rejected any strip that broke near jaws. In addition, we tested samples in their machine directions (MD), and in their cross directions (CD), and we report the results in MD to be succint. max readings were well above the instrument's minimum reading limit of 0.1 N. Then, we divided the measured Fmax by the number of strips to estimate the Fmax value for a single sheet. Standard deviation (s) and standard error (ε) of Fmax values for wet TPs were 0.15, and 0.04, respectively, while the mean (average) Fmax-wet value was 0.26 N for TPs , their mixing ratios, fiber strength, fiber dimensions, as well as, types and amounts of binders and wet strength resins that are used to form a final product collectively influence that product's strength in its dry, and in its wet states. Hence, Fmax quantities varied considerably for TPs in their wet states as indicated by the s and ε values of our measurements.Tensile properties of wet samples were measured according to standard method of ISO 3871: Determination of tensile properties after immersion in water. For very absorbent papers such as TPs, the standard method indicates that only the central part of the test specimen should be wetted. In accordance with this guideline, we rolled around a strip like a circle, and dipped its central area into deionized water for 5 seconds for saturation with water. Then, we fastened the strip to the machine and started the tensile test immediately.  for TPs . Accordi


To investigate the spectrum of antecedent infections in Chinese patients with Guillain‐Barré syndrome (GBS) and analyze the infections‐related clinical phenotypes locally.A prospective case‐control study of 150 patients diagnosed with GBS and age‐ and sex‐matched neurological and healthy controls was performed to investigate recent infections of 14 pathogens serologically and collect the clinical data during a follow‐up of 12 months.Campylobacter jejuni (27%), influenza A (17%) and B (16%), hepatitis A virus (5%), dengue virus (3%), cytomegalovirus (3%), Epstein–Barr virus (3%), Mycoplasma pneumoniae (2%), herpes simplex virus (2%), varicella‐zoster virus (1%), and rubella virus (1%). Serology for infections of hepatitis E virus, Haemophilus influenzae, and Zika virus was negative. There was a higher frequency of C. jejuni, influenza A, influenza B, and hepatitis A virus infections in GBS patients than both the neurological and healthy controls. C. jejuni infection was more frequent in younger GBS patients and was associated with antibodies against GM1, GalNAc‐GD1a, and GM1:galactocerebroside complex. Influenza B infection was associated with a pure motor form of GBS.In total, 53% of patients with GBS had a positive serology for recent infection, including C. jejuni, influenza A, influenza B, and hepatitis A virus serve as the most common cause of antecedent infections in GBS locally. Influenza B‐related GBS may represent a pure motor phenotype. Differences in the infectious spectrum worldwide may contribute to the geographical clinical heterogeneity of GBS. Campylobacter jejuni bearing the gangliosides‐like lipo‐oligosaccharides (LOS) accounts for the pathogenesis of axonal GBS, particularly acute motor axonal neuropathy.Mycoplasma pneumoniae infection is associated with anti‐galactocerebroside  antibodies and pediatric GBS.C. jejuni infection.Guillain‐Barré syndrome (GBS) is an immune‐mediated polyradiculoneuropathy characterized by a rapidly progressive flaccid paresis. Recent evidence supports GBS as a spectrum disorder with regional variation and significant heterogeneity including clinical presentation, electrophysiology, and outcome.This study was performed in the Affiliated Hospital of Jining Medical University, a central hospital regionally in Southwest of Shandong Province, Northern China, where it has a population of 17.1 million with an urban–rural ratio of 1.19. Written informed consent was obtained from all participants, and study procedures were approved by the local Ethics Committee (reference 2013B017 and 2016B006). From October 2013 to June 2017, a total of 150 consecutive patients meeting the diagnostic criteria for GBS and its variantsn = 23), cerebral hemorrhage (n = 27), peripheral vertigo (n = 28), Bell's palsy (n = 39), migraine (n = 15), myasthenia gravis (n = 4), meningitis (n = 3), Parkinson disease (n = 6), and epilepsy (n = 5). The 150 healthy controls were recruited from the same hospital and in all heathy controls, organic diseases were ruled out by the routine medical examination.After the inclusion of each patient with GBS, a sex‐ and age‐matched inpatient with other neurological diseases (OND) and sex‐ and age‐matched healthy donors in the same period were, respectively, selected from the local biological sample bank of the hospital established from July 2012. Among the 150 OND controls were included patients with a cerebral infarction , hepatitis A virus, hepatitis E virus, and Zika virus. The details of ELISA kits for detecting the infectious agents are shown in Table C. jejuni, influenza A, and influenza B virus infections were defined as the presence of IgA and/or IgM antibodies. H. influenzae infection was defined as the presence of IgG antibodies. Infections of M. pneumoniae, hepatitis A virus, herpes simplex virus, varicella‐zoster virus, EBV, dengue virus, rubella virus, CMV, hepatitis E virus, and Zika virus were defined as the presence of IgM antibodies. The serology for specific infections in the controls was detected only if more than five GBS patients were positive for this infection as previously described.A total of 14 infectious agents were selected according to previous reportThe serum samples of patients with GBS were tested in duplicate for IgM and IgG antibodies against GM1, GM2, GM3, GM1b, GD1a, N‐acetylgalactosaminyl GD1a , GD1b, GT1a, GQ1b, GalC, sulfatide, GM1:GalC, GM1:sulfatide, GalC:cholesterol, and GalC:sulfatide complexes as previously described.Our data will be shared by request from any qualified investigator for scientific purposes.P < 0.05 was considered to be significant.Normally distributed continuous data were presented as means and standard deviations. The categorical variables were shown as n (%). The difference in the frequency of infections in patients with GBS and the controls was compared by the Chi‐square test or Fisher's exact test. For patients with and without infections, the difference in demographic and clinical features, anti‐glycolipid antibodies, and clinical subtypes were compared by Chi‐square test or Fisher's exact test. The analysis was performed with the SPSS 20.0 analysis software . A two‐sided C. jejuni , influenza A , influenza B , hepatitis A virus , dengue virus , CMV , EBV , M. pneumoniae , herpes simplex virus , varicella‐zoster virus , and rubella virus . There were significant higher frequencies of C. jejuni, influenza A, influenza B, and hepatitis A virus infections in patients with GBS than in the controls . In addition, these patients with influenza B infection had no ataxia (0/7), no pain (0/7), no demyelinating subtypes (0/5) and high frequency of mechanical ventilation , and pretreatment liver dysfunction . There was no mechanical ventilation (0/11) in GBS patients following influenza A infection. There was no pretreatment liver dysfunction (0/25) in GBS patients following C. jejuni infection. With regard to patients with C. jejuni, influenza A and B virus as well as without infection, there was no difference in frequency of patients on cranial nerve involvement, ataxia, tendon reflex at nadir, pain, mechanical ventilation, electrophysiological classification, and pretreatment liver dysfunction.As shown in Table n = 125, 83%), Miller Fisher syndrome (MFS) , acute ophthalmoparesis , GBS/MFS overlap , bifacial weakness with paraesthesias , acute pharyngeal weakness , and pure sensory subtype . As shown in Figure The patients were classified into GBS n = 15, 83%, MC. jejuni infection than patients without infections . The anti‐GalC:sulfatide complex antibodies were IgG subtype and were detected in one patient with influenza A and M. pneumoniae infections. For patients with anti‐GM1 IgG antibodies, 40% (23/58) had cross‐reaction with GM1:GalC complex and 60% solely bound to GM1. For patients with anti‐GM1:GalC complex IgG antibodies, 26% (9/34) showed complex‐independent, 24% (8/34) showed complex‐enhancement, 18% (6/34) showed complex‐attenuated, and 32% (11/34) showed complex‐dependent. For patients with anti‐GM1:sulfatide complex IgG antibodies, 43% (13/30) showed complex‐independent, 13% (4/30) showed complex‐enhancement, 17% (5/30) showed complex‐attenuated, and 27% (8/30) showed complex‐dependent.As shown in Table C. jejuni, influenza A, influenza B, and hepatitis A virus currently served as the most common cause of antecedent infections in GBS in the Southwest of Shandong Province, Northern China. The proportion of patients following infections of CMV, EBV, and M. pneumoniae only accounted for less than 5% of the total patients, respectively. Infections of dengue virus, herpes simplex virus, varicella‐zoster virus, and rubella virus were also detected but only in a minority of patients and not higher than in controls. The proportion of patients with C. jejuni infection in our region (27%) was similar to those patients reported in Dutch (32%)C. jejuni infection in China may reflect the improved healthy conditions of this country and be related to the rapid development of society and the economy.C. jejuni infection has a strong relation with axonal GBS.C. jejuni infection may contribute to the predominant GBS subtype in China changed from axonal GBS in the 1990s to demyelinating GBS in 2010s. Notably, seven patients with C. jejuni infection complained of upper respiratory tract symptoms. The infection of C. jejuni may breakdown the host immune balance and increase the host susceptibility to the infectious diseases.C. jejuni infection may cause other infections beyond our study, which accounts for the upper respiratory tract symptoms in the patients.We hereby demonstrated that in Dutch 2%3 and tC. jejuni infection had more often complaints of diarrhea than other patients. Although a cohort study from Bangladesh showed no association between the age of patients with GBS and C. jejuni infection,C. jejuni infection was more frequent in younger patients with GBS, which may reflect a special dietary construct increasing the risk of C. jejuni infection in the youth population. Similarly, a recent international study in GBS showed that patients with the axonal subtype are younger than other patients.C. jejuni and other infections. Notably, GBS patients following influenza B infections displayed pure motor deficits and high risk of needing mechanical ventilation  while GBS patients following influenza A infections had no need for mechanical ventilation (0/11) and relatively low frequency of patients with GBS‐DS ≥ 4 at nadir. Our study supported influenza B‐related GBS as a severe phenotype of pure motor deficits while influenza A‐related GBS mainly presents as a mild clinical phenotype. Our results were similar to a previous study that none of influenza A‐related GBS (0/8) needed mechanical ventilation while half of the GBS patients following influenza B infection (2/4) needed mechanical ventilation.Patients with GBS in our cohort study displayed infection‐related clinical features. Being similar to the Dutch study,C. jejuni infection and antibodies against gangliosides, including GM1, GM1b, GD1a, GalNAc‐GD1a, and GQ1b, has been well established in GBS.C. jejuni infection and anti‐GM1, anti‐GalNAc‐GD1a, and anti‐GM1:GalC complex antibodies. The gene polymorphism of cst‐II, encoding a sialyltransferase in C. jejuni, leads to the biosynthesis of different gangliosides‐mimicking LOS.C. jejuni strains with cst‐II (Asn51) regularly express the GQ1b‐like LOS while the strains with cst‐II (Thr51) express more GM1‐like and GD1a‐like LOS.C. jejuni with cst‐II (Thr51), bearing GM1‐like LOS, as one of the causative pathogens in our region, which deserves a further study using C. jejuni samples from the patients. Moreover, none of the patients in our cohort were detected with H. influenzae infection, which was frequently seen in patients with MFS.Previously, the relation between C. jejuni infection had pretreatment liver dysfunction, which needs further confirmation by other cohort studies.Liver injury in patients following influenza A and B infections has been described in both the cohort study and case report.C. jejuni serves as the predominant cause of antecedent infections in patients with GBS in our region, but the frequency is much lower than 30 years ago. The regional infectious spectrum contributed to the clinical heterogeneity of GBS. Our results deserve further confirmation by other larger cohort studies.In conclusion, this is the first study to report the antecedent infectious spectrum in patients with GBS in China. We firstly reported influenza B‐related GBS as a pure motor phenotype. Y. Wang developed the concept and design of the article. Y. Hao, W. Wang and B. Qiao and D. Liu performed the experiment. W. Wang and X. Feng collected the clinical data. M. Chen and Y. Wang analyzed all of the data. Y. Hao and Y. Wang wrote the first draft, B.C. Jacobs and Y. Wang performed the critical revision and all the authors critically evaluated the manuscript.The authors report no disclosures relevant to the manuscript.Table S1. Details of ELISA kits of antecedent infections assay.Table S2. Urban and rural distribution of antecedent infections in patients with Guillain‐Barré syndrome.Table S3. Antecedent infections and antibodies to glycolipids and glycolipid complex in patients with Guillain‐Barré syndrome.Click here for additional data file.


In recent years, the chemical fingerprinting of traditional Chinese medicines and the metabolites in these compounds has been a hot topic. In the present study, the chemical fingerprint of Tianshu tablets (TST) and the metabolic characteristics of compounds in rats after intragastric administration were studied by ultra-high performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry (UPLC/Q-TOF MS). In a preliminary study, 77 chemical components in TST were determined by comparison with retention times, accurate molecular mass, and characteristic fragment ions of the known compounds in the literature and some well-known compounds were analyzed in detail, and the fragmentation pathways for parishins B, gastrodin A, and cnidilide or neocnilide were specifically analyzed. After intragastric administration of TST (4 g/kg) to rats, a total of 61 compounds were detected in plasma samples, including 7 prototypes and 54 metabolites. After further analysis, it was found that these metabolites were subjected to glucuronidation, sulfation, methylation, hydroxylation, dehydrogenation, or mixed metabolic processes. Hydroxylation and glucuronidation were finally confirmed as the main metabolic pathways. This is the first research on the chemical fingerprint and metabolites of TST, which lays a foundation for further investigation of TST. Da Chuanxiong Formula (DCXF) is a well-known and extensively used traditional Chinese medicine (TCM) decoction for the treatment of migraine caused by blood stasis and wind-heat syndrome. It is composed of two herbs, namely, Chuanxiong (Chuanxiong rhizoma) and Tianma (Gastrodiae rhizoma), with a crude weight ratio of 4 : 1. Tianshu tablets (TST) are a representative DCXF preparation that is widely used in clinics for treating the blood stasis type of headache and migraine − ion at m/z 447.1508. Peak X18 produced MS2 base peaks at m/z 269.1028 and 161.0449 corresponding to [M-H-179 Da]−. This suggests that Peak X18 may contain a glucose group and a fructose group. Therefore, we deduced that the molecular structure likely contains sucrose. According to literature reports [X18 as gastrodin A. Peak X23 gave a [M-H]− ion at m/z 727.2091 and had characteristic fragment ions at m/z 459.1156, 441.1045, 423.0937, 397.1142, 369.1188, and 217.0496. Based on previous studies + ion at m/z 195.1378 and fragment ions at m/z 177.1344, 149.1309, and 107.0550. According to previous literature reports + at m/z 223.0963 corresponding to C12H14O4. M1 was found to have major fragment ions in common with senkyunolide D, so M1 is most likely senkyunolide D or 4,7-dihydroxy-3-butylphthalide. Metabolite M2, which eluted at 10.78 min, formed a molecular ion of [M+H]+ at m/z 253.1071 corresponding to C13H16O5. The characteristic production of m/z 235.0963 and 221.0839 was generated by loss of 18 Da and 18 + 14 Da, which implied loss of a H2O group and methyl group. Other product ions were identical to that of M1. Therefore, M2 may be a metabolite of senkyunolide D after hydroxyl and methyl conjugation. Metabolite M3, which eluted at 9.2 min, formed a molecular ion of [M+H]+ at m/z 303.0535 corresponding to C12H14SO7. Its major fragment ions at m/z 285.0430 and 205.0858 were generated by the loss of 18 Da and 18 + 80 Da, which implied a H2O group and sulfate group. Other product ions were identical to that of M1. Therefore, M3 may be a metabolite of senkyunolide D following sulfation. Metabolite M4, which eluted at 10.6 min, formed a molecular ion of [M+H]+ at m/z 399.1285 corresponding to C18H22O10. Its major fragment ion (m/z 223.0969) was generated by a loss of 176 Da, which implied a glucuronide group. Other product ions were identical to that of M1. Therefore, M4 might be a metabolite of senkyunolide D after glucuronidation. Metabolites M5 and M6 appear to correspond to M4 plus 2 Da or 16 Da, respectively. The product ions m/z 225.4427 and m/z 227.0584 have both lost 176 Da. Therefore, M5 might be a metabolite of senkyunolide D after hydrogenation and glucuronidation, while M6 might be a metabolite of senkyunolide D after hydroxylation and glucuronidation (metabolites of M1 and extract ion chromatograms (EICs) are shown in Metabolite M27, which eluted at 14.81 min, formed a molecular ion of [M+H]+ at m/z 193.1222 corresponding to C12H16O2. A major fragment ion was shared with senkyunolide A, suggesting that M27 is prototype of senkyunolide A. Metabolite M28, which eluted at 14.81 min, formed a molecular ion of [M+H]+ at m/z 223.1328 corresponding to C13H18O3. Its major fragment ions m/z 205.1224 and 191.1060 were generated by loss of 18 Da and 18 + 14 Da, which implied loss of a H2O group and methyl group. Other product ions were identical to that of M27. Based on the possible metabolic reactions, M28 might be a metabolite of senkyunolide A after hydroxylation and methylation. Metabolite M29, which eluted at 10.35 min, formed a molecular ion of [M+H]+ at m/z 372.1475 corresponding to C17H25O6NS. Its major fragment ions m/z 209.1269 and 191.1074 were generated by loss of 163 Da and 163 + 18 Da, which implied loss of an acetylcysteine group and H2O group. Other product ions were identical to that of M27. Therefore, M29 may be a metabolite of senkyunolide A after hydroxyl and acetylcysteine conjugation. Metabolite M30, which eluted at 10.60 min, formed a molecular ion of [M+H]+ at m/z 399.1285 corresponding to C18H22O10. Its major fragment ions m/z 223.0969, 205.0847, and 177.0883 were generated by the loss of 176 Da, 176 + 18 Da, and 176 + 18 + 28 Da, which implied loss of a glucuronide group, H2O group, and CO group. Other product ions were identical to that of M27. Therefore, M30 may be a metabolite of senkyunolide A following carboxylation and glucuronidation. Metabolite M31, which eluted at 8.67 min, formed a molecular ion of [M+H]+ at m/z 401.1444 corresponding to C18H24O10. Its major fragment ions m/z 225.1127, 207.1017, and 189.0924 were generated by loss of 176 Da, 176 + 18 Da, and 176 + 18 + 18 Da, which implied loss of a glucuronide group and two H2O groups. Other product ions were identical to that of M27. Therefore, M31 might be a metabolite of senkyunolide A after 2 hydroxylation events and glucuronidation. Metabolite M32, which eluted at 10.54 min, formed a molecular ion of [M+H]+ at m/z 211.1327 corresponding to C12H18O3. Its major fragment ions were m/z 193.1225 and 175.1096. An m/z of 193.1225 (loss of 18 Da) corresponds to senkyunolide A, suggesting that M32 might be a metabolite of senkyunolide A after H2O conjugation. Metabolite M33, which eluted at 9.56 min, formed a molecular ion of [M+H]+ at m/z 225.1119 corresponding to C12H16O4. Its major fragment ions m/z 207.1013 and 189.0914 were generated by loss of 18 Da and 18 + 18 Da, which implied loss of one or two H2O groups. Other product ions were identical to that of M27. Therefore, M33 might be a metabolite of senkyunolide A after 2 hydroxylation events (metabolites of M27 and extracted ion chromatograms (EICs) are shown in Metabolite Sixty-one metabolites were identified in rat plasma. Through the analysis of these 61 metabolites, it was found that hydroxylation and glucuronidation were the main metabolic ways following oral administration of TST. From the identified metabolites, it can be speculated that after absorption of TST by human blood, most of the compounds undergo hydroxylation and glucuronidation, which allow TST to play a positive role in the treatment of migraine and blood stasis headaches. This provides a basis for follow-up research on the medical uses of TST. At the same time, from the information obtained on the metabolites, it can be seen that the main metabolites in positive ion mode of TST are concentrated as chuanxiong lactones, but there are no effective metabolites from Tianma. It is possible that Tianma metabolites are mainly present in the negative ion mode of plasma or in feces, urine, and bile, which requires further study.In this study, UPLC/Q-TOF MS was used to comprehensively determine the chemical fingerprint and metabolic profile of TST after intragastric administration. In the analysis of the chemical constituents of TST, 77 compounds were identified, including 39 compounds identified in negative ion mode and 38 compounds identified in positive ion mode. In order to elucidate the mass spectrometric pyrolysis law of the main compounds in TST, gastrodin A, parishin B, and cnidilide or neocnilide were specifically analyzed, and the results were completely consistent with the results in reference standards and the reported literature. And 61 metabolites of TST in rat plasma were detected, which were mainly metabolites of 7 compounds. Two prototypes  and their metabolites were analyzed in detail, which showed hydroxylation and glucuronidation were the main metabolic pathways following oral administration. This study expanded our understanding of the chemical constituents of TST, studied its metabolic spectrum for the first time, and clarified its main metabolic pathway in plasma, which will lay the foundation for follow-up studies of the pharmacological mechanism of TST.