The Endometriosis Health Profile-30 (EHP-30) is a commonly used tool for assessing the impact of endometriosis on a person’s quality of life. The EHP-30 is a 30-item questionnaire that measures various aspects of endometriosis-related health, including physical symptoms, emotional well-being, and functional impairment.EHP-30 has not yet been evaluated with Turkish patients. Therefore, we aim to develop and validate the Turkish version of EHP-30 in this study.This cross-sectional study was conducted with 281 randomly selected patients from Turkish Endometriosis Patient-Support Groups. The items of the EHP-30 distributed across 5 subscales of the core questionnaire are generally applicable to all women with endometriosis. There are 11 items on the pain scale, 6 on the control and powerlessness scale, 4 on the social support scale, 6 on the emotional well-being scale, and 3 on the self-image scale. The patients were asked to complete the form with brief demographic information and psychometric evaluation included factor analysis, convergent validity, internal consistency, test-retest reliability, data completeness and the determination of floor and ceiling effects.The main outcomes measures were the test-retest reliability, internal consistency, and the assessment of construct validity.102 consecutive cases were analysed with no cases confirming intraluminal disease. Non-specific evidence of endometriosis such as tight angulation of the bowel was found in 36.3%. Following sigmoidoscopy 100 patients proceeded to surgery and the risk of bowel resection during surgery was 4%.In this study, 281 completed questionnaires were included with a return rate of 91%. Data completeness was accepted as excellent on all subscales. Floor effects were found in medical profession (37%), children (32%) and work (31%) modules. No ceiling effects were found. Division of the core questionnaire into five subscales identical to the original EHP-30 was confirmed by factor analysis performed. The intraclass correlation coefficient for agreement varied from 0.822 to 0.914. There was agreement between the EHP-30 and EQ-5D-3L on both of the hypotheses that were tested. There was a statistically significant difference in scores between endometriosis patients and healthy women across in all subscales (p<.01).EHP-30 had not yet been evaluated with Turkish patients and the results of this study demonstrate the validity and reliability of the Turkish translation of the EHP-30 in assessing endometriosis patients’ health- related quality of life.NCT04862364. Endometriosis is a long-term inflammatory disease characterized by the presence of endometrial tissue outside the uterine cavity. It affects approximately 5-10% of at reproductive period. Only 20-25% of endometriosis patients are asymptomatic, up to 80% suffer from chronic pain and 30-50% have infertility .Endometriosis can have a significant impact on a person’s quality of life, causing physical discomfort and affecting their ability to work and engage in daily activities. In addition to the physical symptoms, endometriosis can also take a toll on a person’s mental health. Many women with endometriosis struggle with anxiety, depression and feelings of isolation due to the chronic nature of the condition and its impact on their daily lives. Despite the prevalence of endometriosis, it can take years for a diagnosis to be made, due in part to the lack of awareness about the condition and the difficulty in diagnosing it. This delay in diagnosis can compound the negative impact on a person’s quality of life as they struggle to manage their symptoms without a proper understanding of what is causing them. As a result, endometriosis is seen as a disabling disorder that can have a substantial impact on women’s daily lives, social interactions, sex life and mental health. Patients’ physical, mental and social elements of life affected by a medical condition or its treatment are all included in the multi-domain concept known as health-related quality of life (HRQoL) ) . There is currently no gold standard for assessing HRQoL in endometriosis patients . The ideEndometriosis Health Profile-30 (EHP-30) was developed by Jones et al.  to evaluTo the best of our knowledge, an endometriosis- specific, validated and a reliable instrument to measure HRQoL is not available in Turkey. Therefore, we aimed to develop and validate a Turkish version of the EHP-30 in this study.EHP-30 is a tool to measure different range of effects that endometriosis can have and consists of two parts: a core questionnaire and a modular questionnaire. The 30 items distributed across 5 subscales of the core questionnaire are generally applicable to all women with endometriosis. There are 11 items on the pain scale, 6 on the control and powerlessness scale, 4 on the social support scale, 6,on the emotional well-being scale and 3 on the self- image scale. There are also six extra models with an additional twenty-three items that may or may not be relevant to all women with endometriosis. Work module and sexual relationship addressed in 5 items whereas feelings about the medical profession addressed with 4, both feelings about treatment and feelings about infertility in 3 and the relationship with child/children addressed in 2. No score was assigned to a subscale if any of its items were left unanswered. The objective of the EHP is to assess the amount of self-reported illness. As a result, a conventional 0–100 scale is used, where 0 represents optimal health and 100 represents the worst health status.After obtaining permission from the developer, Oxford University, the study was registered to the ClinicalTrials database with the identifier: NCT04862364. Translation process carried out in the following steps: First two professional independent translators translated the English version of EHP-30 into Turkish. The authors compared the translations of both translators. Minor discordance was detected, and authors then consolidated the two translations into one Turkish version. Then two translators performed back translation. After the backward translation a team consisting of all the authors and both translators reviewed the back translation and the latest form of the Turkish version of EHP-30 was released after the decision of semantic and conceptual equivalence of the terms. Pilot testing was conducted among 30 women between ages 18-45 who have histologically confirmed diagnosis of endometriosis by surgical intervention. All the interviews were face to face and carried out by one of the authors P.Y.B. At the final step the latest version EHP-30 was proofread and the original questionnaire remained unchanged.The study received local ethical approval. . All women were informed of the study’s objectives and informed that their participation was entirely voluntary, and they were allowed to withdraw at any period. The patients were given written instructions to ensure they understood the process and to reassureance about the confidentiality.This cross-sectional study was carried out at Kanuni Sultan Suleyman Research and Training Hospital between January 2020 to January 2021. All women included in the study were randomly selected from Turkish Endometriosis Patient-Support Groups. The patients were asked to complete a form with brief demographic information on their age, marital and reproductive status and family history as well as both the EHP-30 and EQ-5D-3L questionnaires.Sample Size: Estimating that 10% of reproductive-aged women have endometriosis allowed for a sufficient sample size to be determined. OpenSource Epidemiologic Statistics for Public Health (OpenEpi) software was used to determine the sample size. To achieve 80% power and a 95% confidence interval, a sample size of 242 patients is required for the study.Factor Analysis: To analyse the factor structure of the Turkish EHP-30 subscales, principal component factor analysis with varimax rotation was used. Those items with loadings greater than 0.40 were given.Convergent validity: The assessment of construct validity was performed using the European Quality of Life-5 Dimensions -3 questionare (EQ- 5D-3L), which is a widely recognized health-related quality of life (HRQoL) tool that has undergone extensive validation for the Turkish language. It was hypothesized that there would be a significant correlation between the EHP-30 and EQ-5D-3L with respect to the following five sub hypotheses the EHP-30 and EQ-5D-3L with respect to the following five sub hypotheses: EHP-30 subscale pain with EQ-5D-3L subscales pain/discomfort and daily activities; EQ-5D-3L subscale anxiety/depression; EHP-30 Control. The correlation between the two groups was determined using Spearman’s rho.Internal consistency: Each scale’s internal consistency was calculated using Cronbach’s alpha, and scores above 0.70 indicated adequate internal consistency .Test-retest reliability: Test-retest reliability was evaluated by calculating the intraclass correlation coefficient (ICC) for agreement between two questionnaires filled out by the same set of endometriosis patients 1 month apart. Considering that endometriosis complaints may be related to a woman’s menstrual cycle, a 30-day window was selected. The Wilcoxon signed rank test was used to determine the statistical significance of differences in scores between at time points 1 and 2.Descriptive statistics: Data are presented in Mean ± SD. If applicable, data were compared with a t-test or a nonparametric test (Mann-Whitney test) in case of skewed data. All statistical analyses were performed with SPSS 22 for Mac-Os . P values of <.05 were considered statistically significant.The study included 281 completed questionnaires and all participants were Turkish. The patient return rate was 91% and 80 women without any health complaints were selected from those who visited the hospital for routine check-ups. Both the patient group and the healthy women group had comparable age and marital status. Women who were healthy were more likely to be paid employees or volunteers.An excellent data completeness was attained across all subscales. Only 1.7% of responses were absent on the subscales of the modular questionnaire, whereas 0.6% were missing from the core questionnaire. Sixty-one percent of the questions were fulfilled by all the responders. Three out of eight modules in the modular questionnaire revealed floor effects: medical profession (37%), children (32%), and work (31%). There was no ceiling effect.The core questionnaire was divided into five subscales that were identical to those in the original EHP-30, according to factor analysis. The original EHP-30 classified the question about “feeling violent or aggressive” under the emotion subscale, however the present data suggests that it more properly belongs in the social support subscale. Cronbach’s coefficient for the subscales ranged from 0.75 to 0.97. Coefficients were above 0.90 in eight of the eleven subscales.The results of the comparison between the EHP- 30 and the EQ-5D-3L supported both of the tested hypotheses, with a statistically significant difference in scores observed between endometriosis patients and healthy women in all of the EHP-30 subscales (P<.01). The correlations between the EHP-30 and the EQ-5D-3L, as measured by the Spearman correlation coefficients, ranged from 0.44 to 0.63 for all nine sub-hypotheses (P<.01). The highest correlations were seen between similar subscales such as the EHP-30’s pain and the EQ-5D-3L’s pain/ discomfort subscales .47 out of 55 questionnaires (87%) were reperformed to determine test-retest reliability . The ICCThe analysis of the correlation between patients’ subscale pain score for Turkish version of EHP–30 and the pain Visual Analog Scale have showed no statistically significant differences .As one of the well accepted questionnaires used to measure the specific impact of endometriosis on HRQoL, the EHP-30 has been translated into many languages including Chinese, Brazilian, Dutch, Portuguese, Swedish, French and Spanish . When coOur data showed good internal consistency. Test- retest reliability was high (0.822 to 0.914) and the lowest ICC value of the present study was higher when compared with the previously conducted studies  showing One of the limitations of our study was the method of recruitment. In our study, the participants were primarily sourced from the Turkish Endometriosis Patient-Support Group which may lead to a selection bias because women with severe symptoms are more likely to seek help. Another point to consider is any symptom that is attributable to endometriosis may result from another unconfirmed comorbidity since thorough medical evaluation could not be performed.The results of this validation study for the EHP- 30 indicated a high level of data completeness, with no significant floor or ceiling effects. The questionnaire demonstrated good internal consistency and excellent test-retest reliability. These findings confirm that the Turkish version of the EHP-30 is a valid and reliable tool for measuring the health-related quality of life in individuals with endometriosis.


Mycobacterium bovis is the etiologic agent of bovine tuberculosis (BTB), a serious infectious disease in both humans and animals. BTB is a zoonotic disease primarily affecting cattle and occasionally humans infected through close contact with infected hosts or the consumption of unpasteurized dairy products. Zoonotic tuberculosis is strongly associated with poverty and poor hygiene, and low- and middle-income countries bear the brunt of the disease. BTB has been increasingly recognized as a growing public health threat in developing countries. However, the lack of effective surveillance programs in many of these countries poses a barrier to accurately determining the true burden of this disease. Additionally, the control of BTB is threatened by the emergence of drug-resistant strains that affect the effectiveness of current treatment regimens. Here, we analyzed current trends in the epidemiology of the disease as well as the antimicrobial susceptibility patterns of M. bovis in the Middle East and North Africa (MENA) region, a region that includes several developing countries. Following PRISMA guidelines, a total of 90 studies conducted in the MENA region were selected. Our findings revealed that the prevalence of BTB among humans and cattle varied significantly according to the population size and country in the MENA region. Most of the available studies were based on culture and/or PCR strategies and were published without including data on antimicrobial resistance and molecular typing. Our findings highlighted the paramount need for the use of appropriate diagnostic tools and the implementation of sustainable control measures, especially at the human/animal interface, in the MENA region. Mycobacterium bovis, is one of the world’s most neglected zoonotic diseases [M. bovis belongs to the Mycobacterium tuberculosis complex (MTBC), a cluster of genetically related Mycobacterium species that are associated with tuberculosis infections in a wide range of mammals [M. bovis is the most common cause of wildlife tuberculosis, with a morbidity risk reaching up to 15% of tuberculosis cases in humans [M. bovis, both within a country and across borders [Bovine tuberculosis (BTB), caused by diseases ,2. The p mammals . Of all n humans . This spn humans . The mov borders . Notably borders .M. bovis has a heterogeneous profile, developed countries reported a significantly lower incidence of BTB infections compared to data from developing countries. The lack of effective policies to control BTB in many LMICs negatively affects the health of livestock, humans, and ecosystems and potentially increases the burden of this disease [Although the dissemination of  disease . The tra disease ,9,10,11. disease . However disease . To rein disease . These pM. bovis infections in humans and animals is not well defined in the MENA region. Therefore, we searched PubMed, Science Direct, Scopus, and Google Scholar databases for epidemiologic studies on BTB published between 1990 and 2021. We used a combination of words that included “Mycobacterium bovis”, “Bovine”, “MENA countries (as described previously [The burden of eviously )”, “EpidM. bovis has only been reported in humans and animals in eight MENA countries, including Algeria, Egypt, Iraq, Iran, Morocco, Sudan, Turkey, and Tunisia. In other MENA countries, Lebanon, Djibouti, Palestine, and Saudi Arabia, zoonotic tuberculosis has only been reported in humans. The epidemiologic trends of M. bovis infection varied across the MENA countries, likely influenced by the population size, characteristics of the targeted population, the geographical region, and the rigor of the adopted diagnostic tools and investigation methods. Additionally, the heterogeneity of BTB prevalence has been also associated with other factors such as Bacille Calmette-Guérin (BCG) vaccination status, the consumption of unpasteurized dairy products, and the efficiency of national surveillance programs and BTB control measures [A total of 90 studies conducted in the MENA region were reviewed. Most studies have a cross-sectional design , followed by case reports  and longitudinal studies . We found that measures .M. bovis was reported in a cat and a mongoose in Turkey [M. bovis was detected in camels and pigs in Egypt [Cases of BTB were noted from both pulmonary and extrapulmonary sites in animals  and human Turkey  and Egypn Turkey , respectn Turkey , while Min Egypt ,20.M. bovis among animals in the MENA region. Age, gender, animal body condition, immune suppression, crowding, cross-species transmission, grazing practices, feeding system, environment or weather, and physiological and pathological variations are potential factors contributing to the dissemination of zoonotic M. bovis. Female animals are at a greater risk of BTB than males due to lactation, gestation, and parturition [M. bovis infections [Several risk factors for BTB appear to play an essential role in the spread of turition ,22. Crosturition  and Iranturition ,25. Furtturition . People fections .M. bovis ELISA tests are also available, allowing the detection of antibodies against zoonotic tuberculosis in cattle serum and plasma samples [The World Organization for Animal Health (WOAH) has categorized the tuberculin skin test (TST) as a primary screening test for tuberculosis in cattle . TST is  samples . Althoug samples . However samples  and 16.4 samples  in Egypt samples  and 24.2 samples  in Iraq, samples  in Alger samples  in Turke samples  to 82.6% samples  in Egypt samples  in Iraq, samples  in Tunis samples  and 4.3% samples , 8.5% [4 samples  and 26.3 samples , 1.3% [4 samples  and 10.2 samples , 1.7% [4 samples  and 51.3 samples  and 0.2% samples  and 20.8M. bovis in milk samples collected in the MENA region, most studies reported a relatively low prevalence, ranging from 0.004% [M. bovis prevalence in milk samples  is still commonly consumed raw, without pasteurization, in many rural regions and (2) is widely used in the manufacturing of popular dairy products such as cheese and yogurt [Regarding m 0.004%  to 10.2%m 0.004% . Notably samples . Using td yogurt . Taken td yogurt . To prevd yogurt . Currentd yogurt , which dMycobacterium tuberculosis is the primary causative agent of tuberculosis, followed by other MTBC species, including M. bovis. Nationwide estimations in the MENA countries, when available, revealed a relatively low prevalence of M. bovis among tuberculosis patients in some countries  [In humans, ountries . The preectively . Similarulmonary  and 45 pulmonary  tuberculricanum) . In contricanum)  to 92.4%ricanum)  and 5.36ricanum) , to 3.3%ricanum) .M. bovis infections among dairy farm workers [M. bovis infections in dairy workers [The paucity of data and deficiencies in rigorous monitoring along with inappropriate control measures might cause the disease to spread more within the MENA region and beyond. Several factors might promote the spread of BTB among humans in the MENA region. For example, inappropriate hand washing or disinfection following cow handling appears to be a major risk factor for  workers . The con workers ,42,94. T workers . Further workers . These c workers ,95,96,97M. bovis, the detection of polymorphism in pncA or oxyR genes represents a valuable approach [TM and GeneXpert®, were developed for M. bovis identification [Although the reported detection methods in the studies from the MENA countries varied, active tuberculosis infections are still confirmed by mycobacterial culture which is considered the main approach, even for BTB. However, the adoption of molecular assays might be advantageous. For example, comparing molecular assays with microbiological culture revealed that the detection level of PCR-based assays was slightly greater than the conventional culture approach . Moreoveapproach ,120. Recfication .M. bovis is studied by DNA fingerprinting methods such as IS6110 RFLP (Restriction Fragment Length Polymorphism) [6110 copies imposes the need for other complementary tools, such as spoligotyping and Mycobacterial Interspersed Repetitive Units/Variable Number Tandem Repeat (MIRU/VNTR) [M. bovis diagnosis because it provides a higher discriminatory power, facilitating the investigation of MTBC molecular epidemiology and genetic diversity with greater resolution [M. bovis facilitates infection control and tracking processes. An obvious example of the latter is revealing the effect of the animal movement on the appearance of M. bovis in African countries, which was mainly due to cattle delivered from Europe. This cross-border link was detected by using the spoligotyping approach, with SB0120 and SB0121 spoligotypes being the most abundant of M. bovis [Traditionally, the molecular epidemiology of orphism) . DespiteRU/VNTR) ,124. Fursolution . Howeversolution . RegardlM. bovis . SpoligoM. bovis . This geM. bovis ,98,116 aM. bovis in the MENA region is the drug resistant properties of this zoonotic agent. M. bovis has a natural resistance to pyrazinamide, an essential drug for standard short-course anti-tuberculosis therapy in humans. Unfortunately, phenotypic susceptibility to pyrazinamide is often not tested in the MENA region. Since the currently adopted diagnostic tools do not usually differentiate M. bovis from other MTBC species in MENA countries, BTB patients receive inadequate treatment, risking poorer outcomes and enhancing the selection of drug-resistant strains. Additionally, alarming data on drug resistance have been reported recently in the MENA region. Antimicrobial resistance genes were found in isolates retrieved from both infected humans and animals [M. bovis strains were most commonly resistant to rifampicin and isoniazid in several reports from the MENA region [M. bovis strain was first reported in a Turkish patient in 2015, an 8-month-old male infant with nuclear factor-kB essential modulator (NEMO) deficiency [M. bovis strains among buffaloes [M. bovis isolates possessed resistance to both rifampicin and isoniazid due to genetic mutations [rpoB and katG genes were identified in clinical samples from three unrelated individuals who did not respond to the first line of antituberculosis drug therapy [A major factor that might complicate the control of  animals ,127,128.A region ,110,111.uffaloes . In Suda therapy .M. bovis in the MENA region. Despite the limited number of studies dealing with the epidemiology of M. bovis in most MENA countries, the currently available data shows that BTB is not negligible. The circulation of M. bovis in the community, even at a comparatively low prevalence, emphasizes the global and regional calls for appropriate diagnosis and control measures at the animal/human interface. In some MENA countries, the literature suggests that the prevailing conditions might be conducive for the spread of M. bovis in humans and other animals. This is facilitated by several factors, including the lack of information and deficient diagnosis and monitoring systems [M. bovis in the MENA region emphasizes the need to review the current policies and guidelines adopted by public health stakeholders. Particularly, a better detection of zoonotic tuberculosis cases is required via enhancing laboratory capacity, ensuring access to fast and reliable diagnostic tools, raising awareness and expertise of stakeholders, improving food safety, strengthening surveillance , and addressing research gaps. Finally, the implementation of a One Health approach is crucial to control the spread of this disease in the MENA countries and beyond.To our knowledge, this is the first review regarding the epidemiology of  systems ,49. Ther


A probable problem of disconnection between chemical fingerprints and drug effects for TCMs would be contrary to the original intention of fingerprint research, and limits the development and application of fingerprints. In this study, Shenmai injection, as a treatment dosage form of coronary heart disease, shock, and viral myocarditis clinically, was applied as the research object. The fingerprint of Shenmai injection was constructed, and the pharmacodynamic test of antioxidant effect was carried out to obtain quantitative characteristics and pharmacodynamic data. On this basis, a monitoring model based on the HPLC pharmacodynamic fingerprint was established to evaluate the quality of Shenmai injections from different batches and different manufacturers. Results showed that the optimized HPLC method had good repeatability, precision, and stability. A total of 28 characteristic peaks were identified to provide more chemical information. Furthermore, 13 ginsenosides and notoginsenoside have been selected as characteristic components of LC/MS fingerprint method. 8 peaks closely related to antioxidant properties by multiple linear regression method, which were identified as Rg1, Re, Rf, Rb1, and some other ginsenosides using MS analysis. The monitoring model based on HPLC pharmacodynamic fingerprint could successfully identify quality differences for Shenmai injections. Based on the case study of Shenmai injection, the novel and practical fingerprint analytical strategy could be further applied to monitor or predict the quality of TCMs.The online version contains supplementary material available at 10.1186/s13065-023-00920-7. Traditional Chinese medicine (TCM) has played a vital role in disease prevention and treatment in China for thousands of years. TCM injections as a new pharmaceutical form in the modernization of TCM, are also widely applied in clinical work , 2. HoweThe TCM fingerprint atlas refers to a chromatogram that can mark the characteristics of TCMs has been widely accepted nationally and internationally –11. The Pharmacodynamic fingerprint refers to “chemical fingerprints are related to their efficacy” analysis –18, whicred ginseng and Radix Ophiopogonis, and is considered to invigorate Qi to relieve desertion, nourish Yin, and promote saliva production in Chinese medicine. Clinically, this injection is commonly used in treatment of coronary heart disease, shock, and viral myocarditis [202· free radical scavenging methods to test the antioxidant capacity of Shenmai injections. The results show that Shenmai injection has a certain invitro antioxidant capacity, and the activity is concentration-dependent. A recent study also reported that Shenmai injection has antioxidant effects by reducing ROS and eliminating the production of oxidizing effect such as malondialdehyde (MDA), which may decrease the cardiovascular oxidative stress induced by Nitroglycerin (NTG) tolerance [Shenmai injection as a research object has the largest sales among TCMs in China. There are 66 registration certificates for Shenmai Injection according to the CFDA database. It is prepared from carditis –22. Convcarditis –25. Thercarditis . Xiao WHcarditis  used FRAolerance –30. The olerance . The effolerance –34. And olerance , the simolerance . To dateIn this study, high-performance liquid chromatography (HPLC) was used to establish a chemical fingerprint for Shenmai injection. Crystal violet method , 38 was −1, China). It was filtered through a membrane filter with a pore size of 0.22 μm. Crystal violet is purchased from Shanghai Qiangshun Chemical Reagent Co., Ltd . Potassium hydrogen phthalate, 30% hydrogen peroxide, and ferrous sulfate heptahydrate are all purchased from Jiangsu Yonghua Chemical Technology Co., Ltd .Acetonitrile and methanol are all gradient grade . Glacial acetic acid is purchased from Yonghua Chemical Technology Co., Ltd. . Purified water is supplied by Milli-Q Reference. Phosphate buffer is purchased from Shandong Linyi Yong'an Laboratory . For HPLC/MS, we used a 5600 + quadrupole time-of-flight MS (Sciex). We also used a Vis- spectrophotometer , centrifuge , ultrasonicator , and water purifier .The HPLC  equipped with a quaternary gradient pump, online degasser, autosampler, column oven, ultraviolet detector, and ChemStation software were used. The chromatographic column was a ZORBAX SB-CThe HPLC analysis was conducted using the conditions described for Shenmai injection in The National Drug Standards from the CFDA (WS3-B-3428-98-2010Z) . The mobThe basic principle of the clearance rate ·OH of crystal violet spectrophotometric method is as follows:·OH attacks the point of high electron cloud density, and reacts electrophilically with the C=C group in crystal violet to cause crystal violet to fade. ·OH generation the amount can be indirectly measured by capturing the change rate of crystal violet absorbance value. Theoretically, antioxidants can scavenge hydroxyl radicals and increase the absorbance of the system.−1 FeSO4 solution, 0.75 mL of 0.4 mmol L−1 crystal violet, 0.1 mL potassium hydrogen phthalate buffer (PH = 4), and 0.7 mL of a certain concentration of H2O2 solution were added in a 25 mL volumetric flask, dilute to 25 mL with water, then shake well. The absorbance Ab was measured at a certain wavelength after standing for a while, and meanwhile the absorbance A0 at a certain wavelength with no H2O2 solution is measured. The hydroxyl radicals would be generated. The amount is characterized by.1 mL of 1.0 mmol L0 − Ab. If the absorbance AS was measured after a certain volume of Shenmai injection was added, the hydroxyl radical scavenging rate CLR% could be calculated according to Eq. △A = AMS was conducted in both positive and negative ion modes. The scan range was m/z 100–2000. In positive ion mode, the ion source voltage was 5.5 kV, and the ion source temperature was 600 °C. In negative ion mode, the ion source voltage was − 4.5 kV, and the ion source temperature was 550 °C. The gas 1 (air) and gas 2 (air) pressures were set at 50 psi. The curtain gas (nitrogen) pressure was set at 35 psi. The maximum allowable error was ± 5 ppm. The dispersive potential was 100 V and the collision energy was 10 V.PCA is a common multivariate statistical method that reduces the dimensionality to simplify data sets and reduce the number of indices. It is a common pattern recognition method, and is especially useful for evaluating chemical fingerprints. In the present study, the peak area of each identified peak was considered as one dimension in the data set. PCA involves orthogonal transformation of original random variables into new variables that are not related to the original observations . AccordiThe area and retention time data from the characteristic peaks for the 30 samples were standardized, and PCA was performed using the chemometric software Unscrambler 9.7 . xj  and a response variable y by fitting a linear equation [x is associated with a value of the dependent variable y.Multiple linear regression attempts to model the relationship between two or more explanatory variablesequation . Every vb0 is the regression constant; bj  is the regression parameter; e is the random error.In the Eq. Nei coefficient, and support vector machine [xi and yi are components of vector The similarity method uses a certain number of common and featured indices in two samples as a unified measure . Decisio machine , 42, and machine . In thisMethanol–water, methanol-acetic acid–water, methanol-phosphate buffer-water, acetonitrile–water, and acetonitrile–phosphate buffer-water were compared as mobile phase systems. Among these systems, the separation of acetonitrile–phosphate buffer-water is slightly better than the acetonitrile–water system, but it was not easy to maintain the instrument  and had a poor repeatability. The mobile phase system containing methanol  was inferior to mobile phase systems containing acetonitrile. Finally, acetonitrile–water was selected as the mobile phase.With acetonitrile–water as the mobile phase, and 203 nm as the detection wavelength, we investigated the method performance with column temperatures of 25 °C, 30 °C, and 40 °C. The column temperature had a relatively small effect on the fingerprint of the Shenmai injection, and there was only a slight difference in the retention time with changes in the temperature. Therefore, a column temperature of 25 °C (i.e. room temperature) was selected for HPLC.Chromatographic separation is greatly affected by the mobile phase gradient, and optimization of the mobile phase gradient conditions enables good separation of major peaks. In the presents study, using the optimized mobile phase composition and column temperature, we optimized the mobile phase gradient. The optimum mobile phase gradient elution procedure is detailed in Table 18 , mobile phase of acetonitrile–water, injection volume of 20 µL, and the mobile phase gradient shown in Table In summary, the optimum HPLC conditions for analysis of the Shenmai injection were as follows: detection wavelength of 203 nm, column temperature of 25 °C, chromatographic column of ZORBAX SB-CA chromatographic fingerprint for Shenmai injection was established by determining what peaks were characteristic. Among the chromatographic peaks detected for the 30 batches of Shenmai injection from the three manufacturers, 28 peaks were detected in all of the samples. These peaks showed good separation and high peak intensities, and could be used as fingerprint peaks for Shenmai injection , and the dependent variable is the antioxidant value (y), Using PASW Statistics 18 statistical analysis software to establish multiple regression linear equations. Filter out 8 variables, namely Taking the peak area of the 28 common peaks in the HPLC fingerprint of 30 batches of Shenmai injection as the independent variable , the MS results for some components were affected by components from the matrix, such as plasticizers. Consequently, the spectra lacked characteristic fragments or contained new components produced by chemical reactions that occurred during processing. Because of a lack of relevant data in the literature, the structures of seven characteristic peaks  in the spectra were unable to be identified. These unidentified components were thought to form from ginsenoside diol and triol saponins, but further experimental analysis is required to confirm this.1 and PC2, explained 92% of the variance. The distributions of Shenmai injections from the three manufacturers were significantly different in the score plot  for PCA analysis. Two principal components, PClot Fig. . The quaThe fingerprint data for the 30 batches of Shenmai injection from three manufacturers were imported into a similarity evaluation system published by the Chinese Pharmacopoeia Commission.R) was greater than 95%, indicating that between-batch quality differences were small and the quality was stable and uniform.First, the average fingerprints of the Shenmai injections for each manufacturer were used as standard spectra to calculate the similarity among different batches of Shenmai injection from the same manufacturer Table . The obt2. It indicated that indicating that different manufacturers’ quality differences were also small. Observing the specific similarity value, the Shenmai injections produced by manufacturers A and B were similar , whereas the spectral similarity of the Shenmai injections produced by Manufacturer C was relatively poor. This result is consistent with the PCA analysis results.Next, the spectra from all 30 batches of samples were averaged to produce a standard fingerprint and calculate the similarity of the fingerprints of Shenmai injection Table . The simSimilarity analysis by angle cosine in this paper was not sensitive to the change in the concentration of the constituents. When the peak area of fingerprint distribution was wide, the methods are not sensitive to the difference of data. Therefore, the similarity change caused by the change of the characteristic peaks content in the fingerprint could not be accurately evaluated.In summary, results showed the good performance of the quality control framework for Shenmai injection. HPLC pharmacodynamic fingerprint of Shenmai injection enriched chemical and pharmacodynamic information for identification. The number of characteristic peaks was expanded from 16 to 28 compared with the standard method by optimizing the original HPLC method. Among them, 8 peaks identified as Rg1, Re, Rf, Rb1, and some other ginsenosides using MS analysis were closely related to antioxidant properties by MLR method. Furthermore, the monitoring model based on HPLC pharmacodynamic fingerprint could successfully identify differences in quality for Shenmai injections from different manufacturers and different batches.In this study, the HPLC pharmacodynamic fingerprint of Shenmai injection as a quality control strategy was constructed. The optimized HPLC method with good repeatability, precision, and stability provided 28 characteristic peaks, and the pharmacodynamic test of antioxidant effect was carried out to obtain quantitative characteristics and pharmacodynamic data. Among these characteristic peaks, 8 peaks identified as Rg1, Re, Rf, Rb1, and some other ginsenosides using MS analysis, were closely related to antioxidant properties by MLR method. The monitoring model based on HPLC pharmacodynamic fingerprint could successfully identify quality differences for Shenmai injections. The results provide technical support for the basic research on Shenmai injection.Based on this study and correlative reports of the ginsenosides’ bio-activities, further pharmacology tests of the ginsenosides in Shenmai injecion would be designed and the indexes for pharmacodynamic fingerprint could be optimized to improve the quality control efficiency in future research. And the novel and practical HPLC pharmacodynamic fingerprint analytical strategy could be further applied to monitor or predict the quality of TCM injections, which can greatly facilitate the development of quality evaluation, enhance the clinical safety and effectiveness of TCMs.Additional file 1. The HPLC fingerprint evaluation of precision, repeatability, and Stability.


In this study, we explored the influence of molecularinteractionsand solvent evaporation kinetics on the formation of porous structuresin electrospun nanofibers, utilizing polyacrylonitrile (PAN) and polystyrene(PS) as model polymers. The coaxial electrospinning technique wasemployed to control the injection of water and ethylene glycol (EG)as nonsolvents into polymer jets, demonstrating its potential as apowerful tool for manipulating phase separation processes and fabricatingnanofibers with tailored properties. Our findings highlighted thecritical role of intermolecular interactions between nonsolvents andpolymers in governing phase separation and porous structure formation.Additionally, we observed that the size and polarity of nonsolventmolecules affected the phase separation process. Furthermore, solventevaporation kinetics were found to significantly impact phase separation,as evidenced by less distinct porous structures when using a rapidlyevaporating solvent like tetrahydrofuran (THF) instead of dimethylformamide(DMF). This work offers valuable insights into the intricate relationshipbetween molecular interactions and solvent evaporation kinetics duringelectrospinning, providing guidance for researchers developing porousnanofibers with specific characteristics for various applications,including filtration, drug delivery, and tissue engineering. Advances in fabrication strategies and methodologieshave expanded the range of available morphologies and properties ofporous materials, providing the path for novel applications in areassuch as drug delivery, tissue engineering, and regenerative medicine.9 To create porous materials, a variety of techniques have been developed,including electrochemical anodization, freeze-drying, sol–gelprocesses, self-assembly, three-dimensional (3D) printing, and atomiclayer deposition.11 The majority of these methodsrely on templating and phase separation, which are often combinedwith dissolution/extraction, etching, and high-temperature calcinationor pyrolysis to form pores through the selective removal of sacrificialcomponents.16Porous materials have attracted much interestbecause of theirbroad applicability in fields such as filtration, catalysis, and biomedicine.17 Electrospun nanofiber membranescan display two distinct pore types: interfiber and intrafiber pores.18 Interfiber pores, a signature feature of fibrousmembranes, arise naturally in a nonwoven mat during electrospinning.The pore size and shape are adjustable by controlling electrospinningparameters or collection methods.19 Combiningelectrospinning with polymer phase separation techniques enables thefabrication of individual electrospun porous nanofibers.20 Among the various phase separation mechanisms,nonsolvent-induced phase separation (NIPS) emerged as a straightforwardand practical method for generating electrospun porous nanofibers.21 One strategy involves incorporating a nonsolventto form a polymer/solvent/nonsolvent ternary system. Such a systemcan induce porosity in electrospun fibers.22 A crucial aspect of this process is the choice of solvent/nonsolventcombination. It requires a difference in volatility to induce phaseseparation.23 As a result, the constantdecrease in solvent/non-solvent ratio leads to a polymer-rich matrixand dispersed polymer-lean phases, culminating in porosity after ultimateevaporation.25 Researchers have demonstratedthat highly porous polyacrylonitrile (PAN) and polyvinylidene fluoride(PVDF) fibers can be obtained by adding a small amount of water toa polymer/DMF solution before electrospinning.26 Alternatively, simply electrospinning the polymer solutioninto a nonsolvent bath before complete solvent evaporation can induceporosity.27 For example, Seo et al. foundno porosity when electrospinning a control sample from a polycaprolactone/chloroform(PCL/CHL) solution, whereas they successfully fabricated porous PCLfibers by electrospinning the same solution into a water bath.28 Nonetheless, both approaches come with inherentdisadvantages. First, adding a nonsolvent into the polymer solutionmay destabilize the mixture and reduce its spinnability. Second, controllingthe solvent quantity in real-time during electrospinning remains ahurdle. Finally, when electrospinning polymers into a nonsolvent bath,loosely aggregated nanofibers are typically generated, which may beunsuitable for numerous applications that necessitate flat, nonwovenmembranes, such as filtration.32Electrospinning is an electrohydrodynamic atomization method.Ithas been widely recognized as a simple and versatile technique forgenerating continuous nanofibers and producing 3D constructs withhierarchical porosity by stacking nanofibers in an organized or randomfashion.33 which proceeded from outside to inside and could be affectedby the drying state of the nanofibers. Although coaxial electrospinninghas been employed in the fabrication of core-sheath nanofibers34 and, in some cases, to facilitate the electrospinningof specific polymers using a non-electrospinnable fluid,36 to the best of our knowledge, no previous studies have reportedits use to investigate in situ nonsolvent-induced phase separationduring the electrospinning process. In our study, the core fluid containeda nonsolvent for polyacrylonitrile (PAN) and polystyrene (PS), resultingin the formation of pores at various scales in both polymer nanofibers.With the rapid core fluid injection, large hollow channels were alsoobserved. Sometimes, the polymer sheath collapsed upon drying dueto the presence of these sizable internal channels. The injectionof nonsolvent into the polymer jet had a significant impact on theoverall fiber structure, including size, shape, bead formation, andthe spinnability of the polymer. This novel approach distinguishesour study from previous research in the field, offering new insightsinto the fabrication of electrospun porous nanofibers.In this study, we present a unique approach to producing electrospunporous nanofibers by regulating the nonsolvent content within theliquid polymer jet using the coaxial electrospinning technique. Themixing of core and sheath solutions occurs solely within the liquidjet, thus maintaining the stability and spinnability of the polymersolution. Furthermore, nonsolvent-induced phase separation could beadjusted in real-time on individual nanofibers, allowing for a detailedexamination of its impact on the generation of porosity in each nanofiber.Additionally, the diffusion process occurred from the inside out,as opposed to the slower nonsolvent bath diffusion,Mw)of 150,000 and Polystyrene (PS) with an Mw of 350,000 and a number molecular weight (Mn) of approximately 170,000 were procured from Sigma-Aldrichand employed in the preparation of the outer fluid. Anhydrous N,N-dimethylformamide , tetrahydrofuran , and ethylene glycol were utilized for dissolvingthe polymers or formulating the solvent/nonsolvent core fluid. Nofurther purification was conducted on the received chemicals. Water,used in the experiments for preparing the nonsolvent core fluid, wassubjected to purification via a Millipore Direct-Q 8 UV water purificationsystem, resulting in a resistivity of 18.2 MΩ·cm at 25°C.Polyacrylonitrile (PAN) witha weight average molecular weight  was employed to examine thesurface morphology and internal structure of the nanofibers. In orderto reveal their internal structure, the nanofibers were first fracturedin liquid nitrogen at −195.8 °C and subsequently vacuumdried. To enhance their electrical conductivity, all samples underwentsputter-coating with gold for a duration of 30–120 s, dependingon the specific sample. Representative images of the samples werecaptured at an analytical working distance of 7 mm, employing an acceleratingvoltage of 10 kV and a beam current of 0.40 nA. Nanofiber size measurementswere carried out using ImageJ software (NIH) based on the representativeSEM images. Furthermore, the fiber size distribution was statisticallyanalyzed with the aid of OriginPro software (OriginLab).When the nonsolvent injectionrate reached 0.7 mL/h, the electrospinningprocess became unstable, resulting in fewer fibers being produced.The collected nanofibers displayed significantly larger beads 2E. At a 26 However, it is clear that such effects did notcreate any pores on the surface or the internal structure of PAN nanofibers.At a nonsolvent injection rate of 0.1 mL/h, the PAN nanofiber cross-sectionsexhibited an interconnected porous structure, indicative of spinodaldecomposition phase separation.37 Thisnonsolvent-induced phase separation continued to expand to the surfaceof the nanofibers and beads, leading to the formation of rough surfaceswith particle-like domains  asan alternative nonsolvent, possessing a higher boiling point (197°C) than DMF (153 °C). Like water, EG is miscible with DMF.20 Instead, intermolecular interactions betweennonsolvent molecules and polymer chains appear to be key in determiningwhether phase separation occurs in creating porous nanofibers.42 Both water and EG molecules can form hydrogenbonds with the nitrile (−C≡N) groups in PAN, leadingto intermolecular interactions that may induce phase separation.43 However, water, being a small and highly polarmolecule, forms stronger hydrogen bonds due to its size and polarity,whereas EG, a larger and less polar molecule, may not induce phaseseparation as effectively as water in PAN solutions.44 Moreover, the slow evaporation of solvent DMF allowed sufficienttime for the two nonsolvent molecules to penetrate polymer domains,diffuse outside, and evaporate, leaving no significant nonsolvent-richdomains inside nanofibers to form hollow channels.45 Our observations of nanofiber internal structures  as a secondary polymer for this study. PSis a hydrophobic polymer, while water is a highly polar molecule.The intermolecular interactions between the highly polar water moleculesand nonpolar PS molecules are minimal due to the hydrophobic natureof PS, which prevents significant interactions from forming with water.51 PS nanofibers without the injectionof water exhibited internal porosity due to the diffusion of environmentalwater vapor into PS, causing phase separation , as illustratedin 21 Additionally,the lower water permeability in the PS matrix played a crucial rolein determining fiber size.5220According to the nonsolvent-induced phase separationmechanism for the formation of electrospun porous nanofibers, it isessential to maintain a polymer/solvent/nonsolvent ternary solutionfor a specific period to allow the process to complete effectively.If the solvent evaporates too quickly, the phase separation withinthe nanofibers may be insufficient, resulting in less distinct poresin the final nanofiber structure.48 In brief, the rapid evaporationof THF resulted in the condensation of water vapor. The dischargedliquid jet exhibited a strong attraction to the surrounding tiny waterdroplets, causing hard collisions that dented the soft surface andleft shallow holes after water evaporation . THF has alower boiling point (66 °C) than DMF (153 °C), causing itto evaporate more quickly during electrospinning. This faster evaporationcould lead to a faster solidification of the fibers, potentially affectingthe phase separation process. poration 11A. Due poration 11B,C.At higher water injection rates (0.5–0.9mL/h), hollow channelswere observed in PS fibers, which formed due to the accumulation oflarge water-rich domains. The size of these hollow channels increasedslightly with higher core water injection rates, corroborating therapid solidification of the sheath PS matrix. This observation highlightsthat the intermolecular interactions between nonsolvent and polymerare not the sole determining factors in the phase separation process.Instead, factors such as solvent evaporation rate and electrospinningconditions also play crucial roles in determining the final morphologyof the electrospun fibers.Injecting EG into PS significantlyimproved the spinnability ofPS when using THF as the solvent, enabling the production of a largequantity of fibers 12A. HoweIn conclusion, this study demonstratedthe critical role of molecularinteractions and solvent evaporation kinetics in the formation ofelectrospun porous nanofibers using the coaxial electrospinning technique.By investigating the effects of water and EG as nonsolvents on bothPAN and PS nanofibers, we were able to draw the following key findings:(1) The intermolecular interactions between nonsolvents and polymersplayed a crucial role in determining the phase separation and theformation of porous structures. Stronger interactions, such as thosebetween water and PAN, led to less effective phase separation, whileweaker interactions, such as those between water and PS, resultedin more pronounced phase separation and porous structures. (2) Thesize and polarity of nonsolvent molecules also influenced the phaseseparation process. Water, being a smaller and more polar molecule,induced more effective phase separation in PAN solutions comparedto EG, which has a larger size and lower polarity. (3) The evaporationkinetics of the solvent had a significant impact on the phase separationprocess. Replacing DMF with a faster evaporating solvent like THFresulted in less distinct porous structures due to the rapid solidificationof the fibers, leaving insufficient time for the nonsolvent to diffuseinto the polymer solutions. (4) To achieve desired porous structuresin electrospun nanofibers, understanding the molecular interactionsbetween polymers and nonsolvents, as well as controlling solvent evaporationkinetics, is essential. This knowledge allows for the manipulationof phase separation processes and the creation of nanofibers withtailored properties for various applications. This work provides valuableinsights into the complex relationship between molecular interactionsand solvent evaporation kinetics in the electrospinning process. Itoffers guidance for researchers aiming to develop porous nanofiberswith specific characteristics for a wide range of applications infields such as filtration, drug delivery, and tissue engineering.


Nanofibrous Biomaterials for Biomedical Applications.” This Research Topic has aroused the interest of numerous relevant experts and gathered many cutting-edge research advances on nanofiber biomaterials.Nanofibers represent a distinctive class of biomaterials characterized by their high similarity to the 1D structure of the extracellular matrix, coupled with their high porosity and large specific surface area. These unique features bestow the nanofiber biomaterials with great potential in tissue regeneration and disease diagnosis. Owing to great demand on such promising biomaterials, we are delighted to release the Research Topic of “Yamaura et al. fabricated novel peptide amphiphile (PA) nanofibers loaded with transforming growth factor beta-1 (TGF-β1) inhibitor losartan by a self-assembly strategy for cartilage regeneration. The results revealed that losartan exhibited a sustained release from the PA nanofibers over 2 weeks. Furthermore, the losartan-loaded PA nanofibers showed no cytotoxicity and demonstrated the capability to promote ATDC5 cell proliferation. The in vitro studies additionally indicated that PA nanofibers loaded with losartan had significant anti-inflammatory, anti-degenerative, and cartilage regenerative capacity.Zheng et al. investigated the interaction between electrospun yarn scaffolds and three types of cells  to evaluate their potential for meniscus tissue engineering in the absence of growth factors. The electrospun yarn scaffolds showed a pattern of aligned fiber structure, closely resembling the natural structure in the native meniscus. CCK-8 assay results demonstrated that BMSCs, ADSCs, and chondrocytes exhibited robust proliferation over 14 days, and live/dead staining further proved the good cytocompatibility of the scaffolds. Three-dimensional confocal images revealed that the three types of cells could grow along the thickness direction of the electrospun fiber yarn. Moreover, compared with BMSCs and ADSCs, a significant shape change from spindle shape to spherical shape was observed in the articular chondrocytes. The results of Alcian blue staining revealed a substantial presence of glycosaminoglycan (GAG)-rich extracellular matrix in the chondrocyte group signifying the formation of a cartilage lacuna structure.Zheng et al. reported a hydrogel loaded with a major active constituent of epimedium, icariin, and light-responsive carbon nanofibers for treating periodontitis. Under near-infrared (NIR) irradiation, the composite hydrogel showed high efficacy in eradicating both S. aureus and E. coli. In vitro results also demonstrated that the composite hydrogel promoted M1 to M2 shift in RAW264.7 cells by suppressing the expression of inflammatory factor IL-6 and reactive oxygen species (ROS) and concurrently up-regulating the expression of anti-inflammatory factor IL-10. The composite hydrogel additionally significantly promoted the osteogenic differentiation of BMSCs when exposed to NIR. The in vivo results showed that the composite hydrogel alleviated the destruction of alveolar bone. Taken together, the combination of therapeutic drug and photothermal carbon nanofibers within the hydrogel offers a new approach for the management of periodontitis.Ding et al. developed a hydrogel using a blend of polyvinyl alcohol (PVA) and sodium alginate (ALG), which was loaded with silver (Ag) in the nanofiber form for the potential application in wound healing. The Ag based hydrogel showed excellent photothermal effect with the temperature reaching 45.4°C after 10 min light irradiation. In addition, the hydrogel demonstrated favorable compression behavior. More importantly, ascribed to the encapsulation of Ag, the composite hydrogel showed significant antibacterial effect on MRSA and E. coli.Guo et al. proposed photothermal hyaluronic acid (HA) modified multiwalled carbon nanotubes (MWCNT-HA) for accelerating the apoptosis of nasopharyngeal carcinoma cells. The MWCNT-HA showed an obvious photothermal behavior with the temperature reaching 56°C after laser treatment. The in vitro studies confirmed that MWCNT-HA inhibited the proliferation of CNE-1 cells under NIR irradiation. MWCNT-HA could induce cell death by suppressing the mitochondrial pathway in CNE-1 cells.Ren et al. proposed a novel method by using ionic liquids to fabricate hydroxyapatite (HA) nanofibers, and the HA nanofibers were then used as a filler to improve the mechanical properties of a hydrogel. The ultralong HA nanofibers were fabricated and characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). The underlying formation mechanism of the HA nanofibers was then clarified. Both the stretching and compressing experiment results indicated that the HA nanofibers modified hydrogel showed better mechanical performance than that of the pure hydrogel.Tang et al. reported honokiol-loaded titanium dioxide nanotubes (HNK-TNTs) for the treatment of tongue cancer. The hollow structured titanium dioxide nanotubes were prepared by an anodic oxidation method, followed by adsorption of the drug honokiol. The in vitro results showed that HNK-TNTs inhibited the proliferation and migration of CAL-27 cells, and promoted CAL-27 cells apoptosis by increasing the expression levels of apoptosis factors of Bax and Fas.Based on these publications in the Research Topic, we can continue to observe that nanofiber biomaterials have potential for versatile applications, encompassing cartilage regeneration, tissue engineering, bone repair, wound healing, antitumor treatment, antimicrobial interventions, and mechanical strength enhancement. This compilation of articles will provide readers with a broad guidance and ignite their interest in the field of nanofiber biomaterials.


These results are of great significance in understanding the aging mechanism of electric branches in PVDF cable insulation and optimizing the modification of PVDF insulation materials.In this study, the quantum chemical method was used to investigate the microscopic characteristics of α-poly viny difluoride (PVDF) molecules under the influence of an electric field, and the impact of mechanical stress and electric field polarization on the insulation performance of PVDF was analyzed through the material’s structural and space charge characteristics. The findings reveal that long-term polarization of an electric field leads to a gradual decline in stability and a reduction in the energy gap of the front orbital, resulting in the improved conductivity of PVDF molecules and a change in the reactive active site of the molecular chain. When the energy gap reaches a certain value, a chemical bond fracture occurs, with the C-H and C-F bonds at the ends of the backbone breaking first to form free radicals. This process is triggered by an electric field of 8.7414 × 10 PVDF possesses unique piezoelectric, ferroelectric, and thermoelectric properties, as well as a low price, high flexibility, good biocompatibility, excellent aging resistance, and chemical stability ,2. FerroHowever, during the operation of DC cables in power transmission engineering, various factors, such as line faults and equipment switching, can cause the generation and invasion of an operation impulse voltage . MoreoveThe cracking reaction of insulating polymers under the action of an electric field is a relatively complex physicochemical process. Traditional macroscopic experimental techniques have some limitations, so the microscopic dynamics of PVDF breakdown under an electric field cannot be observed intuitively. With the rapid development of computer technology and software engineering, many previous experiments can be further studied at the microscopic level. The theory of quantum mechanics means that molecular simulation technology is not only limited to the study of chemistry, but also extended to electrical, physical, biological and material science and other disciplines, promoting the development of interdisciplinary research and providing a new means for people to understand the material world, in addition to experimental methods and theoretical methods . Many scIn this study, the molecular dynamics simulation method is used to construct a PVDF molecular model, and the semi-empirical method is used to optimize the structure of the model. Different levels of external electric fields are applied in the direction of the main chain of PVDF to study the changes in the total ground state stable energy, the dipole moment, the molecular polarizability, and the space charge of PVDF molecules.Density functional theory is a widely used computational method for studying the electronic structures of multi-electron systems. It has found extensive application in the fields of physics and chemistry, particularly in the study of molecular and condensed matter properties. Density functional theory is widely used in condensed matter physics, computational materials science, and computational chemistry ,28. In tH0 is the corresponding Hamiltonian when no electric field is applied, and Hint is the corresponding Hamiltonian when the external electric field interacts with the molecular system. Under the dipole approximation, the Hamiltonian corresponding to the interaction between the electric field intensity F and the PVDF molecular system can be expressed as in Equation (2).Here, μ is the molecular electric dipole moment and F is the electric field strength. The whole calculation process is completed using the Gaussian09W software package; the Multiwfn 3.7 software [software ,30 and Vsoftware  are usedThe repeating unit of the PVDF polymer is CH2-CF2, as shown in 11 V/m) along the horizontal direction of the molecular chain, respectively. The optimization and single-point energy calculation are carried out, and the microscopic mechanism of the electrical aging of PVDF materials is studied. PVDF has a large molecular mass, and it is impractical as hundreds of thousands of molecules are required to perform simulations under different electric field strengths. In this study, models with different DPs were selected for pre-simulation. According to the results, it was found that the degree of polymerization had little influence on the results of the study. Combined with the previous analysis of the relationship between the aggregation degree and consumption of machine time, it is found that the value of the aggregation degree has little influence on the research content of this paper. Moreover, the purpose of this work is to study the overall effect of an electric field on the polymer, and an intramolecular study is not our primary purpose, so it is not necessary to use molecular models with tens of thousands of degrees of polymerization. Therefore, the α-phase molecular model of PVDF is constructed in this paper, as shown in First, the changes in molecular structure are judged by the bond length, dihedral angle, and geometric structure. Then, the influence of the electric field on molecules is further determined by the molecular dipole moment, polarizability, molecular frontier orbital, and electrostatic potential surface. Finally, infrared spectra are used to verify the above conclusions.R represents the distance between the leftmost and rightmost C atoms of molecular chains, and D represents the angle of twist of molecular chains. The specific changes in the bond lengths and dihedral angles of PVDF molecules are shown in R gradually increases with the increase in the intensity of the external field, particularly when the intensity of the external field increases from 0 to 8.7414 × 109 V/m (0.017 a.u.), which is due to the transfer of positive and negative charges in the molecular system under the action of the electric field, producing the effect of a certain stretching on the molecular chain. D changed from −146.341° to −174.769°, which gradually stretched the molecular structure and reduced the stability of the molecular geometric structure. The dashed circle represents that the chemical bond has been broken, when no external electric field is added, as in 9 V/m (0.017 a.u.), the C-H and C-F bonds at the left and right ends of the backbone are broken, as shown in 9 V/m (0.0175 a.u.), the internal molecular chain is broken, generating free radicals, as shown in Under the action of an external electric field, which is an electric dipole field, the chemical bond length and dihedral angle in the molecules will change accordingly, so as to characterize the change in the molecular geometric structure under the action of an electric field. 9 V/m (0.016 a.u.), the molecular structure appears to have a virtual frequency, which means that the molecular structure has been damaged. Therefore, under the long-term action of the electric field, the stability of the PVDF molecular chain system will become worse. There is an upper limit for the molecular dipole moment. When the external electric field is too large, the dipole moment will break through the limit value, causing the electrons to eliminate the nucleus and form free electrons, which will eventually lead to the breakdown of the insulating medium.The stability of the molecular system is related to the size of the total energy; the smaller the total energy is, the worse the stability of the molecular system is. Dipole moments and polarizability can characterize the spatial configuration and molecular polarity of molecules to some extent. 9 V/m (0.012 a.u.) in the simulation calculation, the optimization does not converge, indicating that the structure is on the verge of failure.In order to analyze the electronic motion characteristics of PVDF, the frontier orbital energy level, energy gap (Eg), and orbital composition of molecules under different external electric fields are calculated, respectively, and the calculation results of the energy level and Eg are shown in 9 V/m (0.006 a.u.), and 6.1704 × 109 V/m (0.012 a.u.), respectively, which can more intuitively reflect the motion characteristics of the space charge at the microscopic level. It can be seen from the distribution of MO map that the HOMO orbital and the LUMO orbital are mainly concentrated on the left end of the molecular chain before the electric field is applied, which is easily attacked by electrophile reagents and electrophilic reactions occur. However, the effect of the external electric field causes the distribution of the molecular front track to change greatly, and the active reaction site of molecules also changes accordingly, as shown in 9 V/m (0.006 a.u.), the LUMO orbital shifts in the opposite direction. When the electric field reaches 6.1704 × 109 V/m (0.012 a.u.), the LUMO orbital moves towards the end of the chain, and the HOMO orbital also moves to the left end of the chain. The left and right sides of the molecular chain show nucleophilic and electrophilic activity, respectively. Without an external electric field, the electrostatic potential distribution on the molecular surface is as shown in 9 V/m (0.012 a.u.), the molecular chain shows a more positive electrostatic potential at the left end and a more negative electrostatic potential at the right end, as shown in 9 V/m (0.012 a.u.), the change in energy level distribution is more obvious. At the same time, the HOMO and LUMO orbital energy levels are very close, and the Eg between the HOMO orbital and LUMO orbital is only 0.95eV. At this time, PVDF will be in the semiconductor state. Electrons can move freely in the valence band and the conduction band to form a current, and the insulation performance of PVDF will fail.In order to analyze the microscopic change characteristics of the space charge inside PVDF under a continuous electric field, this paper uses the changes in the trap energy level, orbital cloud map, and electrostatic potential surface as a basis for discussion. 9 V/m (0.012 a.u.). The contribution of each atomic orbital in the frontier orbital composition of PVDF is analyzed, and the results are shown in 9 V/m (0.012 a.u.), the HOMO and LUMO orbitals are essentially concentrated on both ends of the molecules, enhancing the reaction activity of the molecular chain end. It can be found from To further predict the active reaction sites of molecules, the Hirshfeld method in Multiwfn 3.7 is used for electric field intensities of 0 and 6.1704 × 10The density of states (DOS) mainly refers to the density of the distribution of molecular orbitals at different energy levels. The density of molecular states can intuitively reflect the distribution of hole traps and the electron trap energy level density of molecular orbitals, and each peak can represent the distribution of a trap energy level . The HOM9 V/m (0.015 a.u.), the infrared spectrum does not change greatly, indicating that the intensity of the low electric field has little influence on the molecular structure, and the molecular system still maintains the stability of the structure. However, when the electric field intensity is above 8.2272 × 109 V/m (0.016 a.u.), the infrared spectrogram changes greatly, as shown in −1 and C-F at 678 cm−1 at the end. Virtual frequency does not represent any real vibration; when the structure of the molecules is no longer stable, virtual frequency will appear in the infrared spectrum. When the electric field intensity continues to increase, the virtual frequency appears in the infrared spectrum, indicating that the structure of molecules is not stable and structural damage has occurred. The critical external electric field of the molecular space’s structural destruction is the starting point of insulation material aging, which will inevitably lead to the destruction of cable dielectric materials, thereby reducing the electrical strength of cables and finally causing the polymer insulation breakdown phenomenon.The infrared spectra of PVDF under different electric field intensities are shown in The density functional method was utilized to investigate the microscopic characteristics of molecules inside the dielectric system of a PVDF cable under the influence of an external electric field. The effects of electric field intensity on the molecular structure, the total energy of PVDF materials, the polarization phenomena, the energy gap, and the infrared spectra were examined. The formation mechanism of electric branches within the cable’s dielectric system was analyzed at the microscopic level, leading to the following conclusions.(1) It can be seen from the change in the orbital energy of the molecular front that with the increase in the electric field, the activity is enhanced, and the physicochemical reaction is more likely to occur, which destroys the optimal, stable structure of molecules, so the corresponding infrared spectra will also change.(2) Under the influence of the external electric field, the dipoles of PVDF molecules rotated in a directional manner, generating an equivalent polarized space charge inside the cable’s dielectric system. A higher polarization rate and polarization space charge density were observed with an increased electric field intensity, which had an impact on the dielectric insulation performance.(3) Strong electric fields were found to cause the cleavage and breakage of PVDF molecular chains, with the C-H and C-F bonds at the ends of the molecular chain being the first to break. From the front track and electrostatic potential surface, it was inferred that these chemical bonds had strong chemical reactivity and were more susceptible to reaction. Future modification technology may help to prevent breakdown at these weak points . These f


Escherichia coli, Streptococcus suis, Salmonella sp., Pasteurella multocida, and Bordetella bronchiseptica). We found that Seasonal Auto-Regressive Integrated Moving Average (SARIMA) outperformed five baselines, including Auto-Regressive Moving Average (ARMA) and Auto-Regressive Integrated Moving Average (ARIMA). We hope this study provides valuable tools to predict the AMR burden not only of the pathogens assessed in this study but also of other bacterial pathogens.Antimicrobial resistance (AMR) is arguably one of the major health and economic challenges in our society. A key aspect of tackling AMR is rapid and accurate detection of the emergence and spread of AMR in food animal production, which requires routine AMR surveillance. However, AMR detection can be expensive and time-consuming considering the growth rate of the bacteria and the most commonly used analytical procedures, such as Minimum Inhibitory Concentration (MIC) testing. To mitigate this issue, we utilized machine learning to predict the future AMR burden of bacterial pathogens. We collected pathogen and antimicrobial data from >600 farms in the United States from 2010 to 2021 to generate AMR time series data. Our prediction focused on five bacterial pathogens ( The discovery of antimicrobials is one of the best advances in therapeutic medicine in humans and animals. Over time, microbes have evolved and developed resistance mechanisms against these antimicrobial compounds. Increasing resistance to the available antimicrobials and stagnation of developing novel antimicrobials limit treatment options for patients with infectious diseases. Therefore, the emergence, dissemination, and persistence of microbes that are resistant to existing antimicrobials pose an enormous threat to public and animal health. Antimicrobials are extensively used in the food animal industry to treat bacterial infections and promote health, welfare, and production. According to Food and Drug Administration (FDA), ~80% of all antibiotics in the United States in 2011 were sold for use in animal husbandry, and ~70% of them belonged to the antibiotic classes used in human medicine  is the primary method for detecting AMR and selecting effective antimicrobials against bacterial pathogens, which involves culturing the bacteria in the presence of a panel of various antimicrobials. Effective antimicrobials can be determined by detecting Minimum Inhibitory Concentration (MIC), where antimicrobials with lower MIC values are considered more effective (susceptible) because less of the drug is needed to inhibit bacterial growth. However, these procedures can be expensive and time-consuming, depending on the growth rate of the bacteria and MIC testing procedures. Alternative methods, such as DNA sequencing technologies, are increasingly used to detect AMR at the molecular level, but they require robust bioinformatics tools to evaluate the genomic structure of the microbial resistomes. Thus, most clinical laboratories still depend primarily on conventional AST to conduct clinical therapy and observe AMR over time. Nevertheless, most farms may not have the resources  to perform routine testing to detect AMR and quantify the AMR burden in field settings. Therefore, developing a tool to predict AMR burden based on available data, such as prior AMR information (susceptible/resistance) against common antimicrobials, could be very useful to better inform decision-making about antimicrobial use at the farm level, which consequently helps mitigate AMR.Machine learning has been widely employed for studying AMR, highlighting its importance in predicting resistance levels mainly using features directly from genotypes  prevalent in the studied swine farms using the prior resistance information. The data included the number of tested pathogens with confirmed resistance (based on MIC interpretations) to their corresponding antimicrobials. Instead of direct use of binary (susceptible and resistance) classified data, we generated integrated time series data, i.e., quarterly-based AMR proportions for each of the study pathogens. This approach enabled us to overcome the limitations of missing data over time. We also compared the performance of SARIMA to that of Auto-Regressive Moving Average  of five bacterial pathogens  and time series analysis  from 2010 to 2021 and tested for AMR against a panel of antimicrobials (S) and resistant (R), based on an interpretation report received from the American Association of Veterinary Laboratory Diagnosticians (AAVLD) accredited laboratory in the United States.In this study, we used pathogen and antimicrobial information from >600 farms owned by two swine production systems in the United States. The samples were collected from pigs infected with one of five bacterial pathogens  the resistance time series for each pathogen and antimicrobial as below.For each pathogen, different groups of antimicrobials were employed for experiments see . One chaith quarter . Res in our data.where Res which can be an indicator for the averaged AMR proportions and dynamics of each time series  changes more dynamically than Res  .ARMA, where p and q are the order of the AR and MA parts, respectively  parts , where p and q are the same as for the ARMA model, and d is the degree of differencing. The integrated part refers to the differencing of observations to allow time series to become stationary.Auto-Regressive Moving Average (ARMA) model consists of two parts, such as autoregressive (AR) and moving average (MA) parts Wold, . The modSeasonal Auto-regressive Integrated Moving Average (SARIMA) model S, where  and  are the order of the non-seasonal and seasonal  models, respectively, d and D are the numbers of non-seasonal and seasonal differences, respectively, and S is the periodic seasonality term. Choosing appropriate parameters is a key process for the optimal SARIMA performance. To this end, autocorrelation and partial autocorrelation functions are utilized. To be precise, we first determine non-seasonality components , and then, we find proper seasonal parameters S using autocorrelation function and partial autocorrelation function. Time series datasets often have trends in time series and changes in the statistical structure of the series, which means non-stationarity. To find non-seasonality parameters, trend and seasonality in time series should be removed using differencing techniques. After the removal of trend and seasonality, the autocorrelation function and partial autocorrelation function help determine non-seasonal parameters. Additionally, we also check the p-value between time series data and its lagged time series, and the number of lags with the lowest p-value determines seasonality parameter S for the SARIMA model. However, these steps do not always guarantee finding a specific set of parameters for the optimal SARIMA model. In many cases, parameter exploration using grid search is required, which means that we set some possible candidates for parameters and check the SARIMA model performance to find sets of parameters with the best performance.A typical SARIMA model has seven parameters, referred to as Naïve method is the simplest time series forecasting method where all remaining forecast is set equal to the observation made in the last timestamp as below.F and Y are forecasting and observed times series, respectively. T and T+t are the timestamps of the last observation and the forecast time, respectively.where Seasonal Naïve method is an extension of the Naïve method with a seasonality. It predicts the forecasts based on the same timestamp in the previous cycle as below.s is seasonality and k is completed cycles.where One-lagged prediction methods rely on the most recently acquired data  provides the largest number of data points to work with, and it shows visible seasonality. We have seven parameters to determine as follows: , , and S. After using the differencing method to find parameter d and to remove the trend component in Res, autocorrelation function, partial autocorrelation function, p-value analysis, and parameter exploration were attempted to assessing SARIMA parameters. We choose optimal SARIMA parameters that predict Res with the lowest error.For accurate AMR time series prediction, it is crucial to find appropriate SARIMA parameters  was utilized for this process. We conducted two experiments for ARMA and ARIMA independently because ARMA does not take parameter d into account while ARIMA considers it.Similar to SARIMA, we also employed parameter exploration to find the optimal parameters for ARMA and ARIMA. Res and applied the chosen seven combinations of parameters to other Res to predict the AMR proportions. Specifically, for each Res, seven experiments with different parameter sets were conducted. Each experiment returned a rooted mean squared error as a performance measurement. We also used three baselines as follows: Naïve, Seasonal Naïve , and one-lagged prediction. All baselines also outputted root mean squared error values for each Res. All experiments were conducted in Python (version 3.7.6).We selected seven combinations of parameters from previous analysis on P-value analysis for the Res and its lagged time series with a different number of lags were also used to find the seasonal parameter S. From these, we can determine our parameter S = 12, but other parameters were not found properly from autocorrelation function and partial autocorrelation function analysis. There were no significant patterns of gradual decay or recurring cycles observed in either the autocorrelation or partial autocorrelation plots , i.e., tried to predict the 10% of the last values in Res after being trained with the first 90% of the Res, and a prediction error was reported. With outputted errors, we selected seven parameter combinations that return the lowest rooted mean squared error values because the next best one after these seven has a relatively big gap in the errors from the first seven parameters, and interestingly, our three parameters S are fixed as 12 while seven different  are acquired from In this regard, we explore the set of parameters that output the lowest error estimation measured by rooted mean squared error. In other words, we conducted trial and error for finding appropriate undetermined parameters remained. Our parameter exploration includes integers from 0 to 5 for three parameters Res with the lowest errors, we explored integers from 0 to 5 for all parameters  and  for ARMA and ARIMA, respectively. Each experiment requires 63 and 62 iterations to search independently. In the end, seven sets of  and  that outputted the lowest rooted mean squared error were selected  time series prediction using SARIMA, the seven previously selected SARIMA parameter sets were applied. Each experiment outputted a rooted mean squared error value which represents how good the prediction is, i.e., the lower the rooted mean squared error value, the more accurate the method . For each ARMA and ARIMA, seven parameters were conducted, and the lowest rooted mean squared error values were outputted among seven different experiments. We observed that our SARIMA method showed lower rooted mean squared error values compared to ARMA, ARIMA, and the other three baselines in general. The rooted mean squared error gap between SARIMA and three baselines became bigger when the AMR proportion time series [Res] have greater deviation values . This is because higher deviation implies more fluctuation in AMR proportion time series that are harder to predict. For example, rooted mean squared error values were similar between SARIMA and three baselines for Res (standard deviation: 0.03), while root mean squared error gap became bigger for Res  against their corresponding antimicrobials. The bacterial species assessed in this study were the most prevalent swine bacterial pathogens dispersed within the studied farms, significantly affecting their health, welfare, and productivity. These pathogens can cause various infections in pigs, including respiratory, gastrointestinal, and/or systemic infections, and antimicrobials are the primary mode of therapy and prevention of these infectious diseases (Robbins et al., This study investigated the plausibility of executing data-driven forecasting of the future AMR burden using the available resistance data in >600 swine farms in the United States from 2010 to 2021. AMR burden was quantified quarterly by calculating the proportions of resistant strains of five crucial bacterial pathogens (Escherichia coli and Salmonella sp., showed very high or increasing trends of AMR proportions against Enrofloxacin, Neomycin, Sulfamethoxazole/trimethoprim, and Clindamycin, etc., while Streptococcus suis exhibited low resistance to ampicillin, ceftiofur, enrofloxacin, florfenicol, and tiamulin. Most of the studied antimicrobials are effective against Pasteurella multocida, whereas Bordetella bronchiseptica displayed higher resistance levels against most antimicrobials assessed in our study. Nevertheless, these quarterly based-AMR proportions showed frequent fluctuations in most pathogens against their corresponding antimicrobials throughout the study period (According to this study, we observed distinct temporal trends in AMR proportions for the five pathogens against their corresponding antimicrobials during the study period –5. For ey period –5. HowevEarly detection of emerging AMR and future prediction of AMR burden and trends are vital to comprehend the extent of the threat and implement appropriate antimicrobial interventions and mitigation strategies. Numerous studies have explored various ML algorithms to study AMR using available phenotypic data (López-Lozano et al., There are a few limitations to our study. The AMR data used for prediction were comprised of data from multiple swine farms within the United States. Although these farms were managed under two major swine production systems, individual farms can have different management practices, biosecurity measures, treatment protocols, etc. Previous studies disclosed various factors, such as transportation, farm management, housing conditions, metals consumption, feeding strategies, antimicrobial usage, and co-infections that can affect the spread of antimicrobial-resistant bacteria and the AMR levels in a farm (Mathew et al., This study proposed to use time series methods for the prediction of future AMR burden by constructing the quarterly based AMR proportion times series. The SARIMA approach showed low errors in terms of rooted mean squared error compared with ARMA, ARIMA, and three other forecasting baselines, and it worked even for highly dynamic time series. We believe that our time series prediction can help to advise using appropriate antimicrobials and reduce the risk related to AMR events by predicting anticipation of AMR occurrences in farms or geographical regions. Furthermore, our study may also contribute to the analysis of similar problems and scenarios.beamartinezlopez@ucdavis.edu.The data analyzed in this study is subject to the following licenses/restrictions: The dataset used in this study cannot be publicly available. Requests to access these datasets should be directed to BM-L, JK designed the study, developed the Python codes for experiments, carried out the analysis of experimental results, and wrote the draft of the manuscript. BM-L and RR collected, cleaned, and verified the data. RR contributed to writing the introduction and discussion parts, especially from biological perspectives. AH, CH, SR, and XL helped to justify methodologies in this study and to edit the method explanation part. MC and RCR helped to develop ideas and analyze the results. All authors participated in the discussion and interpretation of the results and read, edited, and approved the final manuscript.