Domoic acid (DA) is a glutaminergic excitatory neurotoxin that causes the morbidity and mortality of California sea lions  and other marine mammals due to a suite of effects mostly on the nervous and cardiac systems. Between 1998 and 2019, 11,737 live-stranded CSL were admitted to The Marine Mammal Center , over 2,000 of which were intoxicated by DA. A plethora of clinical research has been performed over the past 20 years to characterize the range of toxic effects of DA exposure on CSLs, generating the largest dataset on the effects of natural exposure to this toxin in wildlife.In this study, we review published methods for diagnosing DA intoxication, clinical presentation, and treatment of DA-intoxicated CSL and present a practical, reproducible scoring system called the neuroscore (NS) to help assess whether a DA-affected CSL is fit for release to the wild following rehabilitation. Logistic regression models were used to assess the relationships between outcome (released vs. euthanized or died) and multiple variables to predict the outcome for a subset of 92 stranded CSLs.The largest proportion of DA-intoxicated CSLs was adult females (58.6%). The proportions of acute and chronic cases were 63.5 and 36.5% respectively, with 44% of affected CSL released and 56% either dying naturally or euthanized. The average time in rehabilitation was 15.9 days (range 0–169) for all outcomes. The best-performing model  assessing the relationship between outcome and predictor variables consisted of four variables: final NS, change in NS over time, whether the animal began eating in rehabilitation, and the state of nutrition on admission.Our results provide longitudinal information on the symptomatology of CSL intoxicated by domoic acid and suggest that a behavioral scoring system is a useful tool to assess the fitness for the release of DA-intoxicated CSL. Pseudo-nitzschia  that stranded along the California coast following natural exposure. Domoic acid intoxication was first documented in marine mammals in 1998, when over 400 CSL were stranded along the California coast showing neurological signs and acute mortality (Enhydra lutris nereis) and northern fur seals  stranded along the California coast (Domoic acid (DA) is a potent glutaminergic excitatory neurotoxin that is produced by some species of marine diatoms in the genus itzschia , 2. The itzschia , 3. Domoitzschia , 2. Sincitzschia –14. Amonortality , 15. Sinia coast , 17.A decade after the first cases were recognized, a second clinical syndrome was described in CSL: chronic DA toxicosis. As opposed to acute toxicosis, which immediately follows ingestion and absorption, chronic toxicosis is due either to repeated, low-level exposure of the toxin or to the long-lasting effects of past sub-lethal exposure, as no toxin is present in the body at the time of clinical presentation , 18. AcuOver recent years, the differentiation of these two syndromes has become increasingly difficult, presumably due to a combination of increased frequency of DA-producing harmful algal blooms in the California Current Ecosystem, and continued and/or repeated exposure of individual CSL . FollowiIn this study, we review the published methods for the diagnosis of DA toxicosis in CSL as well as the clinical presentation and treatment of DA toxicosis in CSL based on published literature and 20 years of data collected by The Marine Mammal Center (TMMC), a rescue and rehabilitation facility for stranded marine mammals along central and northern California, based in Sausalito . To aid future clinical management of DA toxicosis in CSL, we present a behavioral assessment tool to aid clinicians in determining whether a CSL affected by DA is fit for release.in utero,” “neurologic,” “fur seal,” “marine mammal.” and “ophthalmic”.Search criteria included peer-reviewed journal articles, conference proceedings, internal case definitions, and book chapters that investigated methods for the diagnosis of DA toxicosis in CSL and laboratory animals. Additionally, the effects of DA toxicosis in CSL, laboratory animals, and other marine species, as well as the clinical presentations of DA intoxication, were explored. A set time frame for the publication date was not included in the search criteria, and relevant published literature was included regardless of the publication date. Interrogated databases included Google Scholar and PubMed, as well as an internal list of DA-related publications and book chapters from TMMC. Keywords used to search online databases included “domoic acid,” “sea lion,” “zalophus,” “sea otter,” “cardiac,” “9/L), elevated hematocrit (median = 49.5%), and/or reduced serum cortisol concentration (<20 mg/dL) on admission blood work provided further indication of DA intoxication (TMMC case definition) (Inclusion criteria for antemortem diagnosis of DA toxicosis (acute or chronic) in CSLs were seizures, ataxia, head weaving, tremors, blindness, blepharospasm, reduced responsiveness, coma, and/or abnormal behavior that included disorientation, unusually human-oriented or inquisitive, aggressive behavior, or repetitive behaviors  (TMMC case definition). Relative eosinophilia (>0.68 × 10inition) .Pseudo-nitzschia bloom or elevated DA levels from monitoring programs such as the Southern California Coastal Ocean Observing System (SCCOOS) and the Central and Northern California Ocean Observing System (CeNCOOS). When available, post-mortem lesions in at least one of the sea lions consistent with acute DA toxicosis in the hippocampus provided further evidence for an acute DA intoxication event , typically in poor body condition, and as an isolated event with neurological abnormalities . AntemorTherapy was aimed at controlling symptoms as previously described in the literature and the TMMC pharmacopeia . PhenobaAdjunct therapy to help minimize inflammation and cellular necrosis included an antioxidant, alpha lipoic acid   and an aAs DA is retained in fetal amniotic and allantoic fluids, leading to prolonged persistence in circulation with subsequent progressive disease and fetal developmental abnormalities , 26, aboA retrospective analysis of the clinical presentation, demographics, and survival to release of 2, 447 CSL diagnosed with DA intoxication and admitted to TMMC between 1998 and 2019 was performed. A subset of 92 CSL affected by DA and admitted to TMMC between July 2015 and August 2017 was analyzed to determine the performance of a quantitative behavioral assessment tool, referred to as the neuroscore (NS), in predicting whether a CSL affected by DA was a candidate for release. The subset of CSL was chosen because they all had at least three complete NS performed with the most up-to-date NS and criteria used consistently by experienced TMMC veterinarians. The NS criteria have been adapted over time based on the changing symptomatology of DA intoxication. Stranding data and clinical presentations, a review of the current diagnostic tests available to differentiate and diagnose acute and chronic DA intoxication, and the performance of the NS in helping to predict whether a CSL is fit for release, as well as its limitations, are reported.All animals were stranded along the California coast between approximately 34°22′23′′ N and 40°0′4′′ N and were transported to TMMC for assessment and possible rehabilitation. Physical examinations were performed on all animals upon admission under manual or chemical restraint. Age class was estimated based on body mass, straight body length, tooth development, and the development of the sagittal crest in males . The staA quantitative behavioral assessment tool (NS) aimed at quantifying the severity of DA-associated effects on stranded CSL was developed at TMMC and was performed on CSL diagnosed with DA intoxication as a standardized method to assess the clinical response to treatment. This assessment is similar to the method previously reported , althougDifferences in the proportion of CSL stranding due to DA between age classes, sex, and outcome (released vs. died/euthanized) and in the proportion of acute vs. chronic cases were tested using Pearson's chi-squared test on the full dataset (CSL stranding between 1998 and 2019). Correlations between variables were tested using generalized linear models and likelihood ratio tests, with model specifics provided in Section 3.t-test. As those results were reported separately for acute and chronic cases, we first calculated the overall mean and standard error, considering sample size weighting.We tested whether it was possible to use different variables to predict the outcome (release vs. death) after stranding due to DA on a subset of 92 CSL strandings between 2015 and 2017. Candidate variables included the state of nutrition, straight body length, presence of circulating eosinophilia, diagnosed co-morbidities at admission, and whether the animal began eating while in rehabilitation, in conjunction with the NS results. We report which combination of variables was the best predictors of releasability to aid rehabilitation facilities in determining whether a DA-affected CSL is fit for release (as determined by the low likelihood of re-stranding). Generalized linear models with logit link functions and binomial error distributions were constructed for different combinations of candidate variables, and their performance was compared using 10-fold cross-validation error, AIC, and AUC (area under the curve) . Cross-vP-value cutoff of 0.05. “No support” is used when P-values are high (~0.1 and above), “weak support” when P-values are close to 0.05 (~0.01–0.1), “moderate support” when P-values are small (~0.001–0.01), and “strong support” when P-values are very small (~<0.001). This reporting method emphasizes the fact that statistical significance is determined on a continuum and follows current reporting recommendations  have also been well-documented in the literature (9/L (n = 540) had eosinophilia on admit blood work; 70.6% (n = 293) of acutely intoxicated CSL and 61.7% (n = 140) of chronically intoxicated CSL had an eosinophilia. We found a slightly higher mean eosinophil count of 1.07 × 109/L  compared to previously published data. We found no statistical support for a difference in previously published eosinophil counts (mean = 1.01 × 109/L) and our current study (mean = 1.07 × 109/L), t-test, t = 1.471, df = 670, p-value = 0.142.Various clinical presentations previously described in the literature were observed in CSL with DA intoxication, including, but not limited to, head weaving, ataxia, seizures, and coma that varied in severity depending on the animal. Cardiomyopathy, blindness, and the presence of eosinophilia  of which were diagnosed with DA toxicosis , where, on average, the number of DA-associated strandings increased by 2.1% each year, which may in part be due to an increase in the total CSL population over time  and 36.5% (n = 598), respectively, with strong statistical support for an annual increase of 7.4% of the average proportion of chronic DA stranding . We were unable to categorize a total of 807 cases due to the lack of use of the classification of acute or chronic DA intoxication at admission by the clinician.Between 1998 and 2019, TMMC rescued a total of 11, 737 CSL, 21%  of stranded CSL with DA intoxication (acute or chronic) were released, while 56%  died or were euthanized. Of the animals that died or were euthanized, 42.4% (n = 579) died naturally, and 57.6% (n = 787) were euthanized. A total of 149 animals with DA intoxication re-stranded (6.1%) after being released, a rate that was significantly higher than the re-strand rate due to causes of stranding excluding DA intoxication during this same period . This rate considers each re-strand as a separate event, even if the same animal re-strands multiple times.Between 1998 and 2019, 44% . Most sea lions with DA toxicosis were adult females, followed by juvenile males, subadult males, subadult females, yearling females, and adult males , and 53.2% were released (n = 49). Nine animals that died or were euthanized had full histopathology collected on necropsy, and eight of the nine animals had brain and/or cardiac lesions consistent with domoic acid toxicity, ranging from unilateral to bilateral hippocampal atrophy, inflammation, gliosis, and/or neuronal degeneration; myocardial degeneration, necrosis, or edema. The animal that did not have lesions consistent with domoic acid toxicosis was diagnosed with meningitis , auditory approach response, tactile response, and mentation were the most important. When using only one subsection at a time in a logistic regression model, the subsections that correlated most strongly with outcome were auditory approach response, tactile response, and locomotion.As the survivability of released CSL with DA intoxication is unknown and outside the scope of this study, the re-strand rate was used as an assessment of the effectiveness of the NS in aiding clinicians in determining whether an intoxicated CSL was fit for release. At TMMC, a NS of 10 for the third/final NS performed has been used since 2006 as a cutoff to differentiate between a releasable and non-releasable animal. Prior to the implementation of the NS in the release assessment (1998–2006), the average re-strand rate for DA-intoxicated CSL was 8.2%. In the time frame after the consistent use of the NS during the release assessment (2007–2019), the average re-strand rate was 6%. The differences between the re-strand rates were not statistically supported; however, the consistent implementation of the NS during the release assessment was associated with an improved average re-strand rate for released DA-intoxicated CSL.Despite the extensive research and effort applied to further our understanding of DA intoxication in marine wildlife, humans, and laboratory animal models over the past 20 years, the clinical management of CSL and other marine mammals diagnosed with DA toxicosis remains challenging. Rehabilitation facilities have the responsibility to rehabilitate and release stranded marine mammals with a high “likelihood of survival” post-release, as per NOAA guidelines . We reviOf the previously published diagnostic tests listed in in utero and in the early post-natal phase show that DA exposure causes abnormalities such as repetitive behaviors and altered spontaneous behaviors, a lower seizure threshold, and structural changes in areas of the brain including the hippocampus, cortex, and amygdala (Enhydra lutris) and Guadalupe fur seal  among others , the proportion of CSL with DA intoxication that were released was 62.6%, whereas after the implementation of the NS (2007–2019), the proportion of CSL with DA intoxication that were released decreased to 37.1%. Similarly, the proportion of CSLs that were euthanized prior to the implementation of the NS was 16%, which increased to 41.3% after the NS was implemented. These differences are likely a combination of an improved understanding of the disease process, differing case management styles, suspected repeat DA exposure to CSL over time, thus increasing the proportion of chronically affected CSL with a generally poorer prognosis for survival after release, and the utilization of better tools to help with release assessments.We also assessed whether the NS could be improved based on the results from the subset of 92 CSL by adjusting the relative weights of the NS sections and re-analyzing how accurate the NS was in predicting whether an animal was fit for release. By removing the “Posture” section of the NS entirely and multiplying the “Locomotion” results by three, the NS accuracy improved a small amount from 85 to 87%, although there was no statistical support for this change. The NS has gradually been adjusted over time based on empirical observations of stranded CSL intoxicated by DA and the changing symptomatology over the years since its implementation as an assessment tool for release. However, this study was the first to statistically assess the effectiveness of the NS as a tool for release assessment as well as the optimal weightings between the components of the NS.There were limitations in assessing the NS's accuracy to predict whether DA-intoxicated animals were fit for release, namely that the outcome variable , was often determined by the same clinician treating the animal and performing the NS, and the decision to release an animal was partly based on the same diagnostics used to create the NS. This introduces bias into the current study, but this was unavoidable under the circumstances and does not mean the NS is not useful as it is a quantifiable measure of several variables that clinicians have been using to assess whether an animal is fit for release. Additionally, by analyzing variables outside of the NS, such as the state of nutrition at admission, whether an animal started eating while in rehabilitation, and changes in the NS final score, we aimed to help make the determination more objective for clinicians managing CSL with DA intoxication. Future clinical research could focus on determining the association of the NS with specific lesions in the CSL, such as hippocampal atrophy.in utero and neonatal exposure on the developing fetus and neonate, the pathophysiology of the effects on organ systems outside of the central nervous and cardiac systems, and the long-term effects of repeated non-lethal exposures, among others. This study illustrates the utility of detailed clinical record-keeping, and future work should focus on further refining clinical and diagnostic evaluations of naturally exposed marine mammals to clarify the pathogenesis and prognosis of DA toxicosis in these mammals.While we are continually improving our understanding of DA toxicosis in marine mammals, many challenges remain, including describing and understanding the long-term effects of abby.mcclain@nmmf.org.The datasets presented in this article are not readily available because the current datasets used in this manuscript belong to the Marine Mammal Center and not the corresponding author. Requests can be made through the data request system directly to the Marine Mammal Center to obtain any data from this manuscript. Requests to access the datasets should be directed to AM, Ethical approval was not required for the study involving animals in accordance with the local legislation and institutional requirements because this study was performed using retrospective data collected during routine health care and release assessments for stranded California sea lions undergoing rehabilitation.AM, CF, SJ, SW, and FG contributed to the conception and design of the manuscript. TN organized and collected the data. BB performed the statistical analysis. AM, CF, SJ, SW, LT-B, and FG contributed to the clinical care and management of cases as well as diagnostics. PD contributed to the histopathology and post-mortem review of cases. AM wrote the first draft of the manuscript. BB, CF, SJ, and FG wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.


The increasing survival of patients with breast cancer has prompted the assessment of mortality due to all causes of death in these patients. We estimated the absolute risks of death from different causes, useful for health-care planning and clinical prediction, as well as cause-specific hazards, useful for hypothesis generation on etiology and risk factors.Using data from population-based cancer registries we performed a retrospective study on a cohort of women diagnosed with primary breast cancer. We carried out a competing-cause analysis computing cumulative incidence functions (CIFs) and cause-specific hazards (CSHs) in the whole cohort, separately by age, stage and registry area.The study cohort comprised 12,742 women followed up for six years. Breast cancer showed the highest CIF, 13.71%, and cardiovascular disease was the second leading cause of death with a CIF of 3.60%. The contribution of breast cancer deaths to the CIF for all causes varied widely by age class: 89.25% in women diagnosed at age <50 years, 72.94% in women diagnosed at age 50–69 and 48.25% in women diagnosed at age ≥70. Greater CIF variations were observed according to stage: the contribution of causes other than breast cancer to CIF for all causes was 73.4% in women with stage I disease, 42.9% in stage II–III and only 13.2% in stage IV. CSH computation revealed temporal variations: in women diagnosed at age ≥70 the CSH for breast cancer was equaled by that for cardiovascular disease and “other diseases” in the sixth year following diagnosis, and an early peak for breast cancer was identified in the first year following diagnosis. Among women aged 50–69 we identified an early peak for breast cancer followed by a further peak near the second year of follow-up. Comparison by geographic area highlighted conspicuous variations: the highest CIF for cardiovascular disease was more than 70% higher than the lowest, while for breast cancer the highest CIF doubled the lowest.The integrated interpretation of absolute risks and hazards suggests the need for multidisciplinary surveillance and prevention using community-based, holistic and well-coordinated survivorship care models. For womA systematic review  showed tThe analysis of cause-specific deaths requires specific attention because of the competition between different causes of death. In breast cancer patients the mortality from a specific cause of death, for example CVD, is strongly influenced by breast cancer mortality, as the occurrence of breast cancer death precludes the possibility for a person to die from other diseases.The analysis of competing mortality is useful in two main settings. The first is clinical resource allocation and predictive research; in this case the need is to estimate the absolute risk of dying in patients with a specific disease. The second is the setting of etiology studies, where it is important to study the instantaneous rate of occurrence of the event of interest in subjects still at risk of the event in every instant (hazard). The recommendation from the literature is to use cumulative incidence functions (CIFs) and risk ratios for the estimation of absolute risks, and cause-specific hazards (CSHs) and cause-specific hazard ratios (CSHRs) for the investigation of instantaneous rates –20. CIF As a further study objective we decided to analyze the geographic variations of CIFs and CSHs. To our knowledge only the paper by Ho et al.  reportedWe designed a competing-mortality study taking into account breast cancer deaths, other cancer-related deaths, CVD deaths, respiratory-disease deaths, and deaths from other causes than the above listed. We included all women with breast cancer regardless of age and disease stage. We decided to analyze the data in a relatively recent time span to be able to provide an up-to-date picture of the causes of death following breast cancer. We used a retrospective cohort design based on population-based registries, thereby avoiding any selection bias.22.1This was a retrospective study on a cohort of women diagnosed with primary breast cancer. The cases were archived in the following population-based cancer registries: Aosta Valley (2010–2013), Brindisi (2010–2013), Pavia (2010–2013), Modena (2014–2017), Ragusa and Caltanissetta (2010–2013), Sondrio (2010–2016), South Tyrol (2010–2016) and Trapani (2010–2013). Selection using the site code C50 and malignant epithelial morphology codes M8010–M8575 of the International Classification of Diseases for Oncology (ICD-O-3)  retrieve2.2t and refers to the number of individuals enrolled in the study. In a simplified case – observation without censoring – CIF at time t can be computed as the fraction D/N, where N is the number of individuals under study at time 0 and D is the number of persons who die or develop a disease in a specified time period, from 0 to t. CSH estimates the instantaneous probability at time t of an event, considering as denominator the population surviving up to time point t, thereby providing a picture of the instantaneous modifications in the risk under study. While CIF refers to the initial number of patients, CSH refers to patients surviving at time t. The CSH analysis results are useful to intercept variations in rates, taking into account at every time point the number of people surviving up to that moment and thereby making it possible to analyze determinants in the causes of disease development or progression rates. In survival analysis, risk takes the denomination of CIF and rate is substituted by CSH. We estimated CIFs and CSHs, taking all cases of the cohort together and separately by registry to investigate the extent of geographic variation. We also analyzed CIFs and CSHs separately by age , stage  and registry. Differences in CSH were determined by log-rank test and those in CIF with Gray’s test . Stage information was available for 9131 (71.66%) women; the breakdown by stage I, II–III (grouped together for the study) and IV was 4024 (31.58%), 4418 (34.67%) and 689 (5.41%), respectively. A total of 2760 women died during the first six years, 1630  of breast cancer, 288  of cancers other than breast, 415  of CVD, 76  of respiratory diseases, and 351  of causes other than the above listed.3.2To illustrate the absolute risk of mortality in this breast cancer cohort, Gray’s test reported statistically significant differences of CIFs by age and stage for all five causes-of-death groups. This finding led us to explore CIFs separately for age and stage. CIFs by age are presented in We also performed specific analyses by different combinations of the staging variables T (primary tumor), N  and M (distant metastases), and age (data not shown). The most interesting result was that in older women (≥70 years at diagnosis) with small-size cancers (T1) and no metastases at presentation the CIF for CVD mortality at six years from diagnosis was higher than that for breast cancer, 6.03% versus 5.68%, respectively.3.3CSH estimates by stage are presented in 3.4Gray’s test for subdistribution hazards revealed statistically significant differences in CIF by registry for all five causes-of-death groups, prompting us to compute CIFs by registry  and hazards (CSHs) side by side. Important CIF variations for different causes of death were identified by age class and stage, and the relevance of causes of death other than breast cancer was demonstrated. Analysis of CSHs revealed marked variations during the follow-up period, identifying peaks that were useful to understand the development of all diseases that may affect women with a diagnosis of breast cancer. This information completes the analysis of CIFs, because it shows that diseases other than breast cancer that contribute significantly to the absolute risk of dying (CIF) do not act uniformly during the follow-up period but are more likely to present in specific moments in time.These results support our hypothesis that side-by-side computation of CIFs and CSHs may provide a more complete epidemiologic picture of causes of death following a breast cancer diagnosis. With regard to CIF (a measure of absolute risks), our results pointed in the same direction as studies using similar metrics. Clèries et al. , despiteThe computation of absolute risks allowed us to identify CVD as the second leading cause of death over a six-year follow-up with a CIF of 3.60%, amounting to 15.27% of CIFs for all causes. These results are similar to what Gernaat et al. reported in their review  selectedThe other principal metric we computed was CSH, analyzing it over time since diagnosis. To our knowledge only a paper by Colzani et al.  reportedad hoc studies will be needed.The results of this paper may also be useful to generate hypotheses about disease progression following a breast cancer diagnosis. Breast cancer metastases have been shown to appear at variable intervals , and twoThe differences we observed in CIFs and CSHs could be explored by taking into account exposure to different diets and environmental pollutants. However, these aspects are beyond the scope of this paper, which aims to present the first population-based analysis in Europe using CSHs and CIFs. Further analysis will be performed on the dataset to explain risk factors.A further aim of our study was to investigate the geographic variations of CIF and CSH. CIFs and CSHs showed remarkable differences. For example, the CIF for CVD in the cancer registry with the highest value was more than 70% higher than the CIF for CVD in the cancer registry with the lowest value. To our knowledge the only study that reported variations in cause-specific deaths according to geographic region was the one by Ho et al. . They drA limitation of our study is the presence of “R99”  (n=115) among the ICD-10 mortality codes; however, its percentage, 0.9% of the whole cohort, can hardly be considered to invalidate the results. The analysis of cause-specific mortality may be challenging because of the possible misclassification of causes of death. A study in Italy  on a popA further limitation of the study is that information on breast cancer stage was available for only 71.7% of cases.We decided to observe the follow-up until the sixth year from diagnosis in order to use the most up-to-date data available, which allowed us to describe the most recent epidemiology of the causes of death. However, this choice precluded us from observing what happened from the sixth year onward.A major strength of our study is that for the first time, to our knowledge, CIFs and CSHs were analyzed side by side, enabling us to measure absolute risks and rate variations at the same time. A further strength is the population-based design, which allowed us to describe what happened in the general population of a vast area, taking into account women at whichever age and whichever breast cancer stage. This prevented the introduction of selection bias and enhanced the generalizability of our results. Likewise, we analyzed for the first time in Europe and to our knowledge the second time worldwide geographic variations in the risks and rates of cause-specific mortality. Geographic variations in risks are very important to identify because they may point to a different distribution of modifiable risk factors. The availability of such information may prompt changes in the clinical follow-up of patients and indicate regional differences in the pathologic features of breast cancer. It can also direct etiologic research and be used in the planning of geographically tailored preventive and clinical strategies and resource allocation.The results of this study also suggest considerations in the setting of tertiary prevention because of the weight of non-breast-cancer deaths among women with a breast cancer diagnosis. The first two causes of death we observed were breast cancer and CVD. The risk of disease progression in breast cancer is associated with modifiable factors such as cigarette smoking, obesity, metabolic syndrome and diabetes, high blood pressure and a sedentary lifestyle, with some studies also identifying a link with atmospheric particulate matter exposure –40. BreaThe need to take into account causes of death other than breast cancer in women with a breast cancer diagnosis is also related to survivorship care models. Some authors –44 propo5The results of our competing-cause analysis show that causes of death other than breast cancer are important in women with a diagnosis of breast cancer, especially women aged ≥50 years and those with stage I–III cancer, and that causes of death vary with time and also between registry areas. These results underscore the need for oncologists to balance the types and intensity of breast cancer treatment, taking into account possible cardiovascular and other side effects and the application of differential follow-up pathways. Furthermore, the observed geographic differences warrant research into the association of such differences with risk factors. The integrated interpretation of absolute risks and hazards highlights the necessity of surveillance and prevention by a multidisciplinary approach, and the need for community-based, holistic and well-coordinated survivorship care models.The datasets presented in this article are not readily available because In respect to privacy legislation the dataset could not be accessed. Requests to access the datasets should be directed to alessandro.borgini@istitutotumori.mi.it.The study was approved by the Ethics Committee of Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy. Record number 155/19.AB: Data curation, Investigation, Validation, Writing – original draft. PC: Conceptualization, Formal Analysis, Methodology, Supervision, Writing – original draft. RB: Conceptualization, Writing – review & editing. SF: Data curation, Investigation, Validation, Writing – review & editing. AT: Data curation, Investigation, Writing – original draft. MM: Data curation, Validation, Writing – review & editing. FV: Data curation, Validation, Writing – review & editing. SE: Data curation, Validation, Writing – review & editing. AA: Data curation, Validation, Writing – review & editing. CC: Data curation, Validation, Writing – review & editing. LB: Data curation, Validation, Writing – review & editing. SM: Data curation, Validation, Writing – review & editing. GCas: Data curation, Validation, Writing – review & editing. RT: Data curation, Validation, Writing – review & editing. AF: Data curation, Validation, Writing – review & editing. PG: Data curation, Validation, Writing – review & editing. GCan: Data curation, Validation, Writing – review & editing. TS: Data curation, Validation, Writing – review & editing. MC: Data curation, Validation, Writing – review & editing. SB: Data curation, Validation, Writing – review & editing. GB: Investigation, Software, Writing – review & editing. VP: Validation, Writing – review & editing. CV: Validation, Writing – review & editing. FT: Validation, Writing – review & editing. MC: Validation, Writing – review & editing. GT: Conceptualization, Methodology, Validation, Writing – review & editing.


Direct antihypertensive therapy in hypertensive patients with a high CVD risk can reduce the incidence of cardiovascular death but increase adverse cardiovascular events, so additional ways to identify hypertensive patients at high risk may be needed. Studies have shown that immunity and inflammation affect the prognoses of patients with hypertension and that the pan-immune-inflammation value (PIV) is an index to assess immunity and inflammation, but few studies have applied the PIV index to patients with hypertension.To explore the relationship between the PIV and long-term all-cause and cardiovascular mortality in patients with hypertension.n = 8,938), T2 group , and T3 group . The relationship between the PIV and long-term all-cause and cardiovascular death was assessed by survival curves and Cox regression analysis based on the NHANES recommended weights.Data from the National Health and Nutrition Examination Survey (NHANES) 1999–2018 with a mortality follow-up through December 31, 2019, were analyzed. A total of 26,781 participants were evaluated. The patients were grouped based on PIV levels as follows: T1 group (p < 0.001] and cardiovascular  mortality.The PIV was significantly associated with long-term all-cause and cardiovascular mortality in patients with hypertension. After full adjustment, patients with higher PIV have a higher risk of all-cause [Group 3: HR: 1.37, 95% CI: 1.20–1.55, Elevated PIV was associated with increased all-cause mortality and cardiovascular mortality in hypertensive patients. Hypertension is recognized as one of the major factors affecting the current global burden of disease , and theRecent studies have pointed out that immunity and inflammation are related to the occurrence and development of hypertension. An abnormal immune status will contribute to inflammation and end-organ damage in hypertension , 8. In aThe pan-immune-inflammation value (PIV) is an index that can evaluate the immune and inflammatory status of patients. It incorporates the counts of neutrophils, platelets, monocytes, and lymphocytes. In previous studies, the PIV has been shown to be associated with the prognosis of a variety of diseases related to immunity and inflammation, such as breast cancer , antineuThe purpose of this study was to explore the relationship between the PIV and long-term all-cause mortality and cardiovascular mortality in community hypertension patients so as to provide insight and suggestions for the treatment and management of hypertension in the American Community.The NHANES  is a research program designed to assess the health and nutrition statuses of adults and children in the United States. The program was started in the early 1960s. It is a survey of different populations and health topics. In 1999, the survey became an ongoing program involving a variety of health and nutrition measurements. Each year, the project surveys a nationally representative sample of approximately 5,000 people. The NCHS ethics review board has approved the NHANES protocol. Written informed consent was obtained from each participant.The NHANES interview section includes demographic, socioeconomic, diet, and health-related questions. The physical examination includes physiological measurements, laboratory examination results, and so on. A retrospective analysis was performed using publicly available data from the NHANES from 1999 to 2018.In the NHANES 1999–2018, there were a total of 29,318 hypertensive patients aged >20 years and, of them, 2,497 participants were excluded due to a lack of neutrophils, lymphocyte, monocyte, and platelet counts. In addition, 40 participants were excluded due to lack of the data follow-up. Finally, 26,781 participants were enrolled in our study .According to the question in the NHANES: “Has a doctor ever told you that you have hypertension?” participants who answered “yes” were considered hypertensive. In addition, according to blood pressure data collected by the NHANES, participants with systolic blood pressure (SBP) >130 mmHg or diastolic blood pressure (DBP) >80 mmHg were considered hypertensive . Mean va9/L) * platelet count (109/L) * monocyte count / Lymphocyte count (109/L). Patients were divided into three groups based on the tertials of the PIV: T1 group (≤199), T2 group (>199 and ≤ 350), and T3 group (>350).The PIV was calculated as: neutrophil count  using demographic identifiers.Age, sex, race, and BMI were self-reported by participants. Participants who had smoked more than 100 cigarettes in life or were currently smoking were considered smokers. Participants were considered drinkers if they had consumed an average of one or more drinks per day over the previous 12 months. Metabolic equivalent (MET) were calculated from patients’ self-reported weekly activity time in a manner consistent with previous studies . The Heaχ2 test for categorical variables.The analyses were conducted according to NHANES-recommended weights to calculate the weights for specific groups. Continuous variables were expressed as means (standard error), while categorical variables were presented as counts (percentages). Baseline characteristics of the four groups were compared using an analysis of variance (ANOVA) for continuous variables and an We used Kaplan–Meier and Cox regression analyses to evaluate the associations between the PIV and long-term all-cause and CVD mortality. Both estimates and probabilities were based on weights recommended by the NHANES. Model 1 was a crude model unadjusted for potential confounders. Model 2 was adjusted for age and gender. Model 3 was fully adjusted for potential confounders, include age, gender, race/ethnicity, smoking status, drinking status, BMI, Cr, TG, TC, HEI-2015, MET, DM, CHD, stroke and CHF. Regression cubic splines was used to explore the potential non-linear relationship between PIV and hypertensive patients. In addition, we explored the relationship between the PIV and all-cause and CVD mortality in different subgroups, including age, sex, obesity, smoking status, drinking status and antihypertensive drug. In addition, Neutrophil to lymphocyte ratio (NLR), as a common inflammatory parameter, was included in the study for additional analysis. Finally, to verify the robustness of the results, the diagnostic criteria for hypertension were set at 140/90 mmHg and sensitivity analysis was performed.p-value <0.05 indicated significance for all analyses.All data analyses were performed by using the Survey package of the R software . A two-sided n = 8,938), T2 group , and T3 group . The participants in the group with the highest PIV were older and more likely to be non-Hispanic White 5,127 (77.7%). Compared to the patients in the T1 group, patients in the T3 group had higher BMI [31.01(0.12) kg/㎡], WBC [8.75 (0.03) × 109/L], HB , Cr , and TG  values. The proportion of smokers (53.4%) in the T3 group was higher and more likely combined with DM (22.9%), CHF (5.2%), CHD (6.7%), and stroke (6.0%). There were no significant differences among the three groups regarding gender, drinking status, and TC. More data on the baseline characteristics of the study population are detailed in In our study, there were a total of 26,781 participants. The average age of the participants was 54.5 (0.2) years old, and they were slightly more likely to be male (51.7%). Participants were divided into three groups based on the tertials of the PIV: T1 group (p < 0.001) and CVD  death (Model 1). After full adjusted for age, gender, race, smoking status, drinking status, TG, TC, HEI-2015, MET, BMI, Cr, CHF, CHD, DM, and stroke, compared to the T1 group, the T3 groups has a higher risk of all-cause  and CVD  death  all-cause death and 1,721 (5.1%) CVD deaths occurred. As shown in 1) death . In addi1) death .p < 0.001) and CVD  death. In full adjusted model, the T3 groups has a higher risk of all-cause  and CVD  death  death .After stratifying the participants according to age, gender, obesity, smoking status, and drinking status, the association between PIV and all-cause death  did not change. Compared to the T1 group, the T3 group has a higher risk of all-cause death . The resAfter stratifying the participants according to age, gender, obesity, and smoking status, the association between the PIV and CVD death  did not change. Participants in the T3 group have a higher risk of all-cause and CVD death compared to the T1 group. In addition, our results show that there was an interaction between the PIV and drinking . A high PIV was not significantly associated with the risk of CVD death in non-drinkers . The resFigure 5RCS showed no potential non-linear relationship between PIV and all-cause and CVD death .In this retrospective study, our results showed that the PIV was associated with prognoses in hypertensive patients. A high PIV level is an independent risk factor for all-cause death and CVD mortality in hypertensive patients.One-third of adults worldwide are reported to have hypertension, and the prevalence continues to rise . As a maResearch suggests that hypertension is an immune and inflammatory disease . Blood pThe PIV is an index that combines neutrophils, platelets, monocytes, and lymphocytes and has been considered a comprehensive assessment of the immune and inflammatory statuses in patients in previous studies . PreviouThe association between the PIV and all-cause mortality in hypertensive patients did not change after stratification for age, sex, obesity, smoking status, and alcohol consumption. The risk of long-term all-cause mortality was significantly higher in hypertensive patients with high PIV levels than in those in the other three groups. However, our results showed that high levels of PIV did not affect the risk of CVD death in hypertensive patients who did not drink alcohol. Although the specific mechanism of the interaction between drinking and PIV remains unclear, some previous studies may help explain our results. Several studies have shown that alcohol consumption amplifies the effects of inflammation. For example, studies by Yu Sun et al. point out that alcohol can sensitizes Kupffer cells to TNF-α Over-production . AlcoholIn addition, we further analyzed the effect of NLR on cardiovascular death. In contrast to PIV, platelet and monocyte were not included in the calculation of NLR. Our results found that NLR without platelets and monocytes appeared to be more sensitive to cardiovascular death. But we think that PIV is more appropriate for prognostic assessment of cardiovascular death in the community population. First of all, surface molecules on platelets can interact with other cells and chemokines in activated platelets and cause inflammation thrombosis events and CVD . In addiOur findings further suggest that High levels of PIV are associated with poor outcomes in hypertensive patients. PIV is an indicator that can be calculated from simple blood parameters and can be used as a biomarker of poor prognosis in hypertensive patients. In addition, adding the PVI to further comprehensive assessments of hypertensive patients at high risk of CVD and treating these patients with antihypertensive therapy may be an effective way to effectively balance cardiovascular events with other adverse events.As a retrospective study, our study has some limitations. First, the diagnosis of hypertension and comorbidities is partly based on the self-reports of patients, which may deviate from the actual disease situation. Second, all baseline data were obtained by one blood draw and questionnaire survey, and the patients’ data may change during the long-term follow-up. Third, due to the limitations of the retrospective analysis, we were unable to prove a causal relationship between the PIV and death in hypertensive patients, and further prospective studies are, therefore, needed to validate our conclusions. Fourth, our database is limited by the public database, and some data is missing. For example, detailed data on immune diseases, anti-inflammatory drugs and C-reactive protein.The PIV is an independent risk factor for all-cause mortality and cardiovascular mortality in hypertensive patients. This may provide a theoretical basis for future research on effective ways to include further comprehensive assessments of the PIV in high-risk hypertensive patients with CVD to balance cardiovascular events with other adverse events.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.WS designed the research, is the guarantor of this work, had full access to all of the data used in the study, and takes responsibility for the integrity of the data and the accuracy of the data analysis. BW performed the analyses and wrote the first draft of the manuscript. CZ, SL, YZ, SD, and WS revised the manuscript. All authors read and approved the final manuscript and its submission.This research was funded and supported by Longyan City Science and Technology Plan Project (2022LYF17026).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.https://www.frontiersin.org/articles/10.3389/fcvm.2023.1099427/full#supplementary-materialThe Supplementary material for this article can be found online at: Click here for additional data file.Click here for additional data file.


Filtration is a process that eliminates solid sediments and moisture in olive oil to maintain its shelf life during storage. The influence of filtration on the oil characteristics is linked to many parameters such as chemical and sensory traits, cultivars and filtration systems. After assessing the literature on filtration research, we observed that there are contrasting findings and it is complicated to answer the question of whether to filter or not. An analysis of the influence of different filtration technologies used in extra-virgin olive oil production on the phenolic compounds, volatile fractions, antioxidant activity and sensory characteristics is given in this review. The information compiled could help olive oil producers to enhance extra-virgin olive oil quality and maintain it during storage. Virgin olive oil (VOO) has the characteristic of being an oil produced from fruits and not from seeds. This fact makes it a unique and precious food. Moreover, it is obtained exclusively by mechanical and physical processes such as washing and crushing of olive fruits, malaxation of olive paste, centrifugation and facultative filtration before oil packaging . Accordiθ), is controlled by the Hagen Poiseuille equation [Fresh virgin olive oil contains amounts of micro-droplets of vegetation water and solid dispersed particles . This giequation :θ = ΔP/µ (αωV/A + r)1/A dV/dA = surface of the filter;θ = filtration rate (volume of filtrate per unit time);dV/dΔP = difference of pressures at the two sides of the filter medium;μ = viscosity;α = a coefficient due to the filtered resistance that has accumulated in the medium;w = content of solids in the filtrate in weight per unit of volume;r = resistance of the filter medium;θ. Therefore, in practice, a very notable role is mainly played by the surface of the filter. As is known, the temperature heavily affects viscosity. As the temperature increases, the viscosity decreases and the filtration rate increases proportionally. Thus, the filtration rate is in inverse proportion to the oil viscosity [From the analysis of the Hagen-Poiseuille equation, it can be observed that an increase in the filter area, A, is correlated to an increase in the filtration speed dV/discosity . This paiscosity  highlighiscosity . In the olive oil industry, different types of filtration systems can be applied: conventional filtration systems (filter tanks and filter presses), cross-flow filtration , inert gas-flow filtration systems and filter bags . ConventThe characteristic of this method is based on introducing a constant inert gas flow squarely through the olive oil mass during filtration. In this way, it is possible to obtain two advantages: the gas movement makes the precipitation of the suspended solids easy and, at the end of the filtration, the olive oil is already under inert gas that, with the reduction in oxygen, prolongs the shelf life of the product .The presence of phenolic compounds in olive oil is ever-topical and a topic of great interest, both for their antioxidant and nutraceutical properties and for the high stability that they provide to olive oil during storage, both of which are sensory characteristics ,35,36,37p < 0.05) apart from the decarboxylated ligstroside aglycone, which decreases. Data recorded a significant increase (p < 0.05) for the filtered olive oil, mainly of oleuropein aglycone , with values of 72.30 vs. 36.19 mg/kg in unfiltered samples. In filtered oils, the dialdehydic form of elenolic acid linked to hydroxytyrosol  had a content of 13.26 vs. 10.20 mg/kg of the unfiltered sample, such as the ligstroside aglycone (p-HPEA-EA) which showed an increasing amount in filtered oils in comparison to unfiltered ones (28.45 vs. 21.89 mg/kg). The above data have been explained by the authors considering that the removal of water, caused by the filtration process, affected individual phenolic compounds differently as, within the same family, specific chemical characteristics caused different reactions in the filtered oils. Kishimoto [w/w) and solid particles (0.23% w/w) and the highest mean turbidity value , whereas the filtered samples showed an almost complete lack of water (0.05% w/w), no solid particle content and the lowest degree of turbidity . Due to the affinity of phenolic compounds for the water phase, the removal of water through a filtration process decreased the total phenolic content by approximately 20%. The total phenolic content of the unfiltered samples was higher than the filtered ones (708 mg vs. 559 mg tyrosol/kg). With the aim of extending the studies on this topic, some researchers [These compounds can generate the corresponding dialdehydic forms which, in turn, decarboxylate into the respective aglycones . These results are partially in agreement with those reported by Jabeur et al.  who founishimoto  comparedishimoto , the autishimoto  proposedishimoto  who founishimoto , who invishimoto ,39. A siishimoto . The autearchers  for threearchers , explainearchers  who obseearchers .Volatile compounds are a complicated blend of aldehydes, alcohols, ketones, acids, hydrocarbons, and esters and are closely associated with both positive and negative sensory attributes . As descMeanwhile, in Črna oils a significant decrease in the totals of alcohols, aldehydes, ketones and C5 volatile compounds was detected. In fact, in Črna filtered-oil samples a significant decrease of 34% in relation to unfiltered ones for total alcohol concentration  was found. Moreover, in Črna filtered oils, the total amount of aldehydes increased by 9.6% in comparison to unfiltered samples, especially E-2-hexanal with values of 19.962 vs. 21.952 mg/kg, respectively. The filtration process had no significant influence on the total C6 volatiles for both Buža and Črna oils. However, the total of C5 volatile compounds for Črna oils decreased significantly by 4.9% in filtered versus unfiltered oils. The above data were explained by the authors considering that the filtration process had a diverse influence depending on the different varieties of olives. They put forward as possible causes both the complex release mechanism between the oil and water phases and the different amounts of tissue particles removed through filtration. Similar results were also obtained by Fortini et al.  with hisBoth phenolic and volatile compounds affect the sensory features of virgin olive oils. The influence of the filtration process on these substances is also reflected in the sensory traits . This asValli et al.  highlighThe literature analysis revealed that the effects of the filtration process on the quality and shelf life of olive oil are contentious. There is a controversy among the researchers since several authors have reported advantages ,26,38,45Future trends could be to assess the influence of different filtration systems, choosing the most suitable system for the diverse olive cultivars based on their chemical characteristics, such as polyphenolic content. In our opinion, it would be appropriate to conduct further investigations to assess and characterize the chemical and sensory traits of the olive oil from different cultivars, before and after filtration and during storage, using diverse filtration systems. To furnish a clear answer for whether to filter or not, future studies should investigate the use of industrial-scale filtration systems and also evaluate, among the modern methods, the ones with environmental sustainability. Ultimately, the optimization of the operating conditions in the filtration process could be considered by olive oil producers to improve the overall quality level and maintain it during storage.


Childhood maltreatment has been identified as a risk factor for depressive symptoms. Social anxiety is closely associated with depression. Physical activity has been regarded as an underlying protective factor. Little is known about the complex relations among these factors in Chinese middle school students. This study aimed to explore whether social anxiety mediated the association between childhood maltreatment and depressive symptoms and investigate whether physical activity moderated the indirect or direct effect of the mediation model.A total of 1,570 middle school students were recruited and measured for childhood maltreatment (measured by Childhood Trauma Questionnaire—Short Form Chinese version), social anxiety , depressive symptoms , physical activity (as the moderator), and covariates such as age, sex, and nationality. The proposed relationships were tested using mediation and moderated mediation models.Emotional abuse was directly associated with depression, and the association between emotional abuse and depression was partially mediated by social anxiety. The associations between emotional abuse with depression and with social anxiety were moderated by physical activity.This study revealed the mediating role of social anxiety and the moderating role of physical activity between emotional abuse and depression, which emphasizes the potential benefits of sufficient physical activity to reduce social anxiety and depressive symptoms, and more intervention studies should be conducted to explore the direct influence of sufficient physical activity in the future. Childhood maltreatment (CM) is a kind of trauma that children and adolescents aged 0 to 17 suffered from their caregivers, often including physical, sexual, and emotional violence or neglect . Nearly vs. 27.1 years old), and more likely to be chronic (OR = 2.05) and treatment-resistant (OR = 1.90). The severity of depressive symptoms was most prominently associated with emotional abuse  is prevalent in American adolescents and had a prevalence of 9.1% in 2010 . The peap = 0.001) in longitudinal studies  is considered an important protective factor for depressive symptoms  in both  studies .Taken together, CM, SA, and PA all play important roles in endorsing depressive symptoms. Still, the potential influence of these variables on depression is not clear among Chinese middle school students. Hence, this study aims to explore whether SA mediates the association between CM and depressive symptoms and evaluate the moderated role of PA. In this moderated mediation model, we hypothesized that SA might work as a mediator between CM and depressive symptoms, and PA plays a moderator role in the direct and/or indirect effects of CM on depressive symptoms.www.wjx.cn), a professional Chinese online survey management tool, and distributed through the WeChat platform with the help of school teachers. Participants could scan the QR code or click the link of the questionnaire to fill in. All students and their parents have signed informed consent online. A total of 1,785 students were invited to participate; 55 students refused to participate and 160 students were excluded from the analysis due to incomplete data. A total of 1,570 students were included in the following analysis. The response rate was 87.96%. This study was approved by the ethics committee of the Second Xiangya Hospital of Central South University.In this cross-sectional study, by clustering sampling, students of age from 11 to 16 years in a middle school in Changsha, Hunan province, China, were invited to participate. The electronic questionnaires were created online by Wenjuanxing  Chinese version, translated from the English version of CTQ-SF, which was constructed by Bernstein et al. . CTQ-SF Social anxiety was assessed by the Chinese simplified version of the Social Anxiety Scale for Adolescents (SAS-A). Social Anxiety Scale for Adolescents (SAS-A) was compiled by La Greca and Lopez and contained 18 items . The ChiDepressive symptoms  were assessed by the depression subscale of the Chinese version of Depression Anxiety Stress Scales-21 (DASS-21) . The oriPhysical activities (PA) were measured by a question adapted from the Youth Risk Behavior Survey (YRBS) : “How maDemographic characteristics, such as age, sex, and nationality, were collected as covariates. Among these, 1,570 students (aged 13.10 ± 0.95) completed the whole questionnaire and were involved in the analysis; 833 (53.06%) were male students, 737 (46.94%) were female students, 1,490 (94.90%) were Han, and 80 (5.10%) were other nationalities.p < 0.05 (two-tailed) was set as the significance level. Harman's single-factor test was conducted to assess common method bias. Spearman correlation analyses were used to analyze the correlations between variables such as CM, SA, depression, and PA. The moderated mediation analysis was conducted by the SPSS PROCESS 4.1 compiled by Hayes. The association between CM and depression mediated by SA was tested by model 4. The moderated effect of PA on the mediated model was tested by model 59 , and a value of model 59 . BootstrAmong these 1,571 students, 326 (20.76%) students practiced sufficient PA for the past week, and 1,244 (79.24%) had low PA. The prevalence of depressive symptoms in this population of middle school students was 34.59% .Harman's single-factor test showed that in the exploratory factor analysis, there were seven factors with characteristic roots greater than one. The first principal component explained 30.74% of the total variance, which was lower than the critical value of 40% . It indiAfter testing each subscale of CTQ-SF, we find one significant moderated mediation model as shown in p < 0.001), and SA was also significantly positively associated with depression . The direct effect of EA on depression was statistically significant  (https://yilinandrewang.shinyapps.io/pwrSEM/), the mediation model showed a strong statistical power (power = 1.00) , and the direct effect was estimated as 0.44 95% CI 0.39, 0.48). EA was positively associated with SA  . After c, 0.48. EAfter controlling for covariates, the results of the moderated effect of PA are shown in To test how the different levels of PA affected EA on depression, we divided PA into two levels, “low PA” and “sufficient PA”, according to the WHO standard . The dirThis study examined the mediating role of SA between CM and depression and explored the relationships among CM, SA, PA, and depressive symptoms via a moderated mediation model. These findings indicated that CM, SA, and PA were all significantly correlated to depressive symptoms, but the effects were different. SA mediated the association between EA and depressive symptoms. Moreover, the direct effect of CM on depressive symptoms and the path from EA to depressive symptoms was moderated by PA. The results support the importance of PA as a potential protective factor for adolescents to overcome the effect of EA on getting depressive symptoms and SA.Different forms of EA, such as blaming, threatening, frightening, discriminating against, humiliating, or ridiculing , were reConsistent with previous studies, our study also showed the benefits of PA; to be specific, PA moderated the path from EA to depressive symptoms, and EA to SA, and the moderation effect of sufficient PA was stronger than low PA level. A meta-analysis of prospective cohort studies revealed that people with high levels of PA were less likely to develop depression (OR = 0.83) in youths, adults, and older adults . PA was In this study, we investigated CM and explored its association between SA, depression, and PA in a young population of children and adolescents aged 13.10 ± 0.95, showing their relationships in the early stages of children's development. Several limitations associated with this study should be noted. First, we cannot draw any causality between those factors in this cross-sectional study. Second, CM was collected retrospectively, which may introduce recall bias; sexual abuse, a significant form of CM, was not examined in this study; and future studies should endeavor to measure all of the five subtypes of CM. Third, the use of self-report scales to assess whether students meet the WHO PA standard missed more details about PA; future studies should utilize measurement tools that are more objective to improve the representativeness. Moreover, all data were collected from the same middle school in China, which makes it difficult to generalize to other samples. Additionally, though psychotherapy is a valuable intervention for depression, access to psychotherapy may be hard, and psychotherapy was not investigated in this study. Future research should also consider more potential confounding factors associated with depression, such as conditions of receiving psychotherapy, cognition styles, and bullying.This study revealed the mediation effect of social anxiety on the development of emotional abuse to depressive symptoms in Chinese middle school students. Physical activity played a vital moderation role in the path from EA to SA and depression. For students who suffer from EA, it might be essential to get more sufficient PA to reduce SA and depressive symptoms. Getting enough PA is a possible efficient way to minimize the effects of emotional abuse, for both the general population and clinical populations as an additional non-drug treatment.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Ethics Committee of the Second Xiangya Hospital of Central South University. Written informed consent to participate in this study was provided by the participants and the participants' legal guardian/next of kin.XL, YS, and XJ were responsible for the study design. HX, YS, and XL were responsible for recruiting the participants. HX and XJ were involved in statistical analysis. HX wrote the first draft of the manuscript. XJ, XL, and YS wrote sections of the manuscript. All authors have contributed to the manuscript revision, read and approved the final manuscript, and agreed to submit it.


Background and Objectives: The goal of this study was to investigate the effect of selective serotonin reuptake inhibitor treatment on the ovarian reserves of women of reproductive age with major depressive disorder. Materials and Methods: The current study is a prospective controlled trial including 48 women with major depressive disorder and 48 age-matched healthy controls. Ovarian reserve tests are performed prior to treatment and after six cycles of selective serotonin reuptake inhibitor treatment in the major depressive disorder group. Serum follicle-stimulating hormone, luteinizing hormone, estradiol, and anti-Müllerian hormone levels were evaluated from blood samples, and endometrial thickness, total antral follicle count, and volume of both ovaries were assessed using transvaginal ultrasonography. Results: When the first measurements were compared, menstrual duration and menstrual bleeding increased  and luteinizing hormone decreased (p = 0.045) in the major depressive disorder group, while follicle-stimulating hormone, estradiol, anti-Müllerian hormone, endometrial thickness, total antral follicle count, and mean ovarian volume did not differ significantly between groups (p > 0.05). When the major depressive disorder group’s first and final measurements were compared, follicle-stimulating hormone, estradiol, and endometrial thickness increased , luteinizing hormone remained constant (p = 0.541), and anti-Müllerian hormone and total antral follicle count decreased . Conclusions: In this study, we observed that the ovarian reserve test results of patients diagnosed with major depression for the first time after 6 months of SSRI treatment were significantly different from the results of the pretreatment and control groups. Depression affects 7.4% of adults in the United States between the ages of 18 and 39, with women (9.3%) being more affected than men 5.8%) . Accordi.8% . AccThe number and quality of oocytes present in a woman’s ovarian reserve (OR) determine her reproductive potential. Many tests have been studied to evaluate OR ,7. In woInfertility rates have risen in recent years, paralleling the rise in depression rates among women of reproductive age. In addition, SSRIs are widely used in the treatment of depression. There are numerous reasons for the rise in infertility rates; we hypothesize that the presence of depression and the use of antidepressants is one of them. Therefore, in this study, we aimed to evaluate OR tests before and after antidepressant treatment in women of reproductive age who were diagnosed with depression for the first episode. The obtained data were compared with the data of the control group, consisting of healthy women. This case-controlled prospective study was carried out at Pamukkale University Hospital’s Obstetrics and Gynecology Clinic from November 2020 to July 2022, after ethics approval from the Pamukkale University Local Ethics Committee . Prior to taking part in the study, all participants gave written and informed consent.Women of reproductive age (18–35 years) who applied to the psychiatry clinic and were diagnosed with first-episode MDD using the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM 5) diagnostic criteria, and who were prescribed SSRI antidepressants, were referred to the study center of the gynecology clinic before treatment to be included in our study. In addition, healthy volunteer women of reproductive age (18–35 years) who applied to the gynecology outpatient clinic for a routine gynecological examination were referred to the study center to be included in the control group.Exclusion criteria were: a previous history of SSRI use, a diagnosis of infertility, known serious chronic diseases , urogenital tract infection, existing malignant diseases, polycystic ovarian syndrome (PCOS), use of anticoagulants, use of drugs that affect or alter the sex hormone profile, and alcohol use. A total of 168 women of reproductive age who were consecutively referred to the study center in the gynecology clinic were evaluated for study eligibility. Among them, three women with a diagnosis of infertility, nine women were diagnosed with pelvic pathologies , eight women with systemic diseases, seven women with acute infections, eight women who regularly used combination oral contraceptives (COCs), four women who used anticoagulants, 10 women whose treatment was changed due to drug side effects after starting SSRI antidepressant treatment, 12 women without regular menstrual cycles at the six-month follow-up after starting antidepressant therapy, five women who did not attend the follow-up examination after six cycles, and six women who later refused to participate were excluded. Thus, in total, 48 women with regular menstrual cycles  and who were diagnosed with MDD were assigned to the MDD group, while 48 women who had regular menstrual cycles  without depression or any known medical disease were assigned to the control group . Patients with regular medicament were included in the study. Sertraline, fluoxetine, and escitalopram were the SSRIs used in the patient group. The SSRI doses were used in accordance with the treatment guide and were also the most commonly used doses . In the MDD group, 40 cases were treated with sertraline, 5 with fluoxetine, and 3 with escitalopram. The Hamilton Depression Rating Scale (HAM-D)  was admi2) was calculated after height and weight were measured. Participants were asked to complete a self-assessment questionnaire that recorded demographic information as well as clinical menstrual characteristics. Body mass index , E2, and AMH levels were measured in blood samples, and all transvaginal USGs were performed on the same day as the blood sampling. Endometrial thickness (ET), total AFC, and the volume of both ovaries were all measured using transvaginal USG. The ET was measured at the thickest point of the longitudinal segment. Follicle sizes were calculated by taking the average of the diameter measurements in three planes, and follicles with diameters ranging from 2 to 10 mm were considered antral. After measuring the diameters of each ovary in three vertical planes, the ovarian volumes were calculated using the formula D1 × D2 × D3 × 0.52. All cases in the MDD group started using SSRI antidepressants prescribed by the psychiatrist after the above examinations and evaluations were performed by the gynecologist. Following six cycles (roughly six months), on the third to the fifth day of their menstrual cycles, serum FSH, LH, E2, and AMH levels were re-evaluated after a 12-h fast, and the same researcher performed a transvaginal USG. All ET, total AFC, and ovarian volume measurements were repeated using transvaginal USG, and all results were recorded.Following a 12-h fast, venous blood samples were collected from healthy volunteer women in the control group on the third to the fifth day of their cycles. The serum levels of FSH, LH, E2, and AMH were measured, and transvaginal USG was performed in all cases on the same day the serum samples were collected by the same researcher. As in the MDD group, following six cycles (roughly six months), on the third to the fifth day of their menstrual cycles, serum FSH, LH, E2, and AMH levels were re-evaluated after a 12-h fast, and the same investigator performed a transvaginal USG. Antidepressants were not prescribed because the control group consisted of healthy women who did not have MDD. Blood samples from the MDD and control groups were taken from the peripheral vein to determine serum AMH levels, which were measured using the Elecsys  AMH kit. The coefficients of variation for intra- and inter-assays were found to be 2.7 and 4.4%, respectively. p-values less than 0.05 were considered statistically significant. The correlation coefficients and significance were calculated via the Spearman test in the evaluation of the relationships between the ordinal variables, at least one of which showed an abnormal distribution.SPSS 25.0 was used to perform all statistical analyses. ). Continuous variables were expressed using the mean, standard deviation (SD), and median (IQR: 25th–75th percentiles), while categorical variables were expressed using frequencies and percentages. Normality was determined using the Shapiro-Wilk test. When the parametric test assumptions were met, the independent samples test-test was used for group comparisons. When the parametric test assumptions were violated, the Mann—Whitney U test was used to compare independent groups. A parametric paired-samples test-test and a non-parametric Wilcoxon signed-rank test were used for pairwise comparisons; This study was carried out in accordance with the Helsinki Declaration’s principles. All participants provided written and informed consent prior to taking part in this study. The study was approved by the Pamukkale University Clinical Research Ethics Committee . p = 0.355, 0.312, and 0.644, respectively), or menstrual length (p = 0.46). Before treatment, MDD patients had significantly higher menstrual duration (days) and menstrual bleeding (pads/day) than controls .As shown in p = 0.063). In the final measurements, it was observed that the MDD group’s values were significantly higher than those of the control group (p = 0.006). In the in-group examinations, the MDD group showed a significant increase (p = 0.05), while the control group showed no statistically significant change (p = 0.679). Furthermore, no statistically significant difference in delta values . In both, it was observed that the values of the MDD group were significantly lower than those of the control group, but no significant change was observed in both groups following the in-group examinations . Furthermore, no statistically significant difference in delta values existed between the two groups . In the final measurements, it was observed that the values of the MDD group were significantly higher than those of the control group (p = 0.021). In the in-group examinations, a significant increase was observed in the MDD group (p = 0.0001), while any change in the control group was not statistically significant (p = 0.278). In the delta values, the change in the MDD group was found to be significantly higher than in the control group . In the final measurements, it was observed that the values of the MDD group were significantly lower than those of the control group (p = 0.009). In the in-group examinations, a significant decrease was observed in the MDD group (p = 0.024), while any change in the control group was not statistically significant (p = 0.495). Furthermore, no statistically significant difference in delta values existed between the two groups . In the in-group examinations, a significant increase was observed in the MDD group (p = 0.005), while any change in the control group was not statistically significant (p = 0.819). Furthermore, in terms of delta values, the change in the MDD group was significantly greater than in the control group . In the final measurements, it was observed that the values of the MDD group were significantly lower than those of the control group (p = 0.018). In the in-group examinations, a significant decrease was observed in the MDD group (p = 0.042), while any change in the control group was not statistically significant (p = 0.415). Furthermore, no statistically significant difference in delta values existed between the two groups . In the final measurements, it was observed that the values of the MDD group were significantly lower than those of the control group (p = 0.036). Furthermore, no significant difference was found between the two groups in the in-group examinations , and the delta values did not differ statistically between the two groups , this relationship was not found in the MDD group (p = 0.597). While there was a statistically significant and positive relationship between the AMH change and BMI values in the control group (p = 0.023), this relationship was not observed in the MDD group (p = 0.176). In the control group, there was a statistically significant and positive relationship between the change in total AFC and BMI values (p = 0.038), and it was observed that the same relationship existed in the MDD group (p = 0.025). While there was a statistically significant and positive relationship between ovarian volume change and BMI values in the control group (p = 0.031), this relationship was not observed in the MDD group (p = 0.261), and while there was a statistically significant and positive relationship between FSH change and menstrual length in the MDD group (p = 0.019), this relationship was not found in the control group . In turn, the earlier increase in FSH levels stimulates an earlier onset of new follicular growth and an increase in E2 concentrations, ultimately shortening the follicular phase and the overall cycle. These hormone tests are, therefore, used as markers of ovarian reserve ,14. Multiple studies ,16 have Because of their consistent efficacy and favorable safety profile, SSRIs are now widely used in the treatment of a variety of psychiatric disorders. These drugs, however, can have serious side effects such as gastrointestinal bleeding and sexual dysfunction ,25. In tSome limitations of the present study should be considered. The following study limitations were identified: (1) this was a single-center study; (2) a group with a diagnosis of infertility was not included; (3) a group of patients with untreated major depression was not included; (4) a group with irregular menstrual cycles after SSRI treatment was not included; (5) cases with leiomyoma, endometrioma, and PCOS were not evaluated; and (6) cases were assessed after only six months. In conclusion, the rise in infertility rates paralleled by the rise in depression rates among women of reproductive age has led us to believe that there may be a link between these two conditions. In the current study, pretreatment LH levels and menstrual characteristics of non-infertile depressive women were significantly altered compared to the control group. In addition, the FSH, E2, and AMH levels, as well as ET and total AFC measurements of depressive women after SSRI treatment, were significantly altered compared to pretreatment. Because we were unable to establish a patient group with untreated major depression, we cannot determine whether these changes were caused by major depression or by SSRIs. However, our findings suggest that SSRIs may also affect these outcomes. More research is needed to confirm our findings.


Ophiopogon japonicus samples from five major production areas in China were analyzed by NIR spectroscopy, and divided into 2127 from Zhejiang and 1530 from other areas (‘non-Zhejiang’). Principal component analysis (PCA) was selected to screen outliers and eliminate them. Monte Carlo cross validation (MCCV) was introduced to divide the training set and test set according to a ratio of 3:7. The raw spectra were preprocessed by nine single and partial combination methods such as the standard normal variable (SNV) and derivative, and then modeled by partial least squares regression (PLSR), a support vector machine (SVM), and soft independent modeling of class analogies (SIMCA). The effects of different pretreatment and chemometrics methods on the model are discussed. The results showed that the three pattern recognition methods were effective in geographical origin tracing, and selecting the appropriate preprocessing method could improve the traceability accuracy. The accuracy of PLSR after the standard normal variable was better, with R2 reaching 0.9979, while that of the second derivative was the lowest with an R2 of 0.9656. After the SNV pretreatment, the accuracy of the training set and test set of SVM reached the highest values, which were 99.73% and 98.40%, respectively. The accuracy of SIMCA pretreated with SNV and MSC was the highest for the origin traceability of Ophiopogon japonicus, which could reach 100%. The distance between the two classification models of SIMCA-SNV and SIMCA-MSC is greater than 3, indicating that the SIMCA model has good performance.This paper presents a method for the protected geographical indication discrimination of Ophiopogon japonicus from Zhejiang and elsewhere using near-infrared (NIR) spectroscopy combined with chemometrics. A total of 3657  Ophiopogon japonicus is the dried tuberous root of Ophiopogon japonicus (Thunb.) Ker.-Gawl. (family Liliaceae), mainly produced in Sichuan, Zhejiang, Hubei and Anhui provinces [Ophiopogon japonicus has, for example, antitumor, anti-inflammatory, hypoglycemic, and antiaging effects, and it can be used in the treatment of diabetes [Ophiopogon japonicus, compatible with red ginseng and schisandra chinensis, can be made into Shengmai Yin, which is widely used in the treatment of acute myocardial infarction, cardiogenic shock, arrhythmia, and other heart diseases [Ophiopogon japonicus is not only a kind of traditional Chinese medicine (TCM), but is also a typical homologous product of medicine and food. It has been used as a health food for a long time to enhance human immunity and soothe the mind [rovinces . Its mairovinces . Modern diabetes ,4. Ophiodiseases . Ophiopothe mind .Ophiopogon japonicus is mostly cultivated in China, with common cultivation areas in Sichuan, Zhejiang, Hubei, Anhui and other provinces. The Ophiopogonis japonicus of Zhejiang is one of the eight traditional medicinal materials in Zhejiang. While the Ophiopogonis japonicus of Zhejiang is three years old, all the other Ophiopogonis japonicus are annual, which makes the quality of Zhejiang Ophiopogonis japonicus much higher than that produced elsewhere [Ophiopogon japonicus with UPLC/Q-TOF MS, and found that there were significant differences in the chemical composition of Ophiopogon japonicus from different production origins [Ophiopogon japonicus of Zhejiang is higher. It also contains borneoside, which has the function of anti-myocardial ischemia [Ophiopogon japonicus of Zhejiang is better than that of other producing areas, which makes its price much higher [Ophiopogon japonicus of Zhejiang is about 500–600 yuan per kg, 5 times higher than that of non-Zhejiang Ophiopogon japonicus. As such, non-Zhejiang Ophiopogon japonicus often appears in the market as from Zhejiang. Most of the Ophiopogon japonicus on the market is sold in powder form, which makes it very difficult to distinguish and discriminate its origins. The discrimination of the protected geographical indication of Ophiopogon japonicus can not only combat fake and shoddy products, but can also provide reference for the traceability of other traditional Chinese medicines.At present, lsewhere . Lyu et  origins . The conischemia  and is nischemia . To sum h higher . AccordiOphiopogon japonicus using HPLC, an ultraviolet spectrophotometer (UV) and an evaporative light scattering detector (ELSD) [Ophiopogon japonicus had different similarities and characteristic peaks that could be effectively distinguished. Chromatographic and mass spectrometry combined with a chemometrics method has the advantages of high sensitivity, good stability, and reproducibility, but its operation process involves a large number of extraction and purification steps, which is complicated and difficult to operate [There are many common methods for the origin tracing of traditional Chinese medicines, including stable isotope techniques ,13, highr (ELSD) . After s operate . DNA bar operate .Near-infrared (NIR) spectroscopy is a rapid on-line identification and analysis method that can scan solids directly and has the advantages of being fast, non-contact, and non-destructive . HoweverOphiopogon japonicus. There are many kinds of spectral pretreatment methods commonly used at present, such as first derivative (1D) [Spectral data are susceptible to stray light, noise, baseline drift, and other factors, thus affecting modeling results . The quaive (1D) , second ive (1D) , Savitzkive (1D) ,35, stanive (1D) ,37, multive (1D) ,39, waveive (1D) , orthogoive (1D) ,42, normive (1D) , and staive (1D) . Differeive (1D) . S-G smoive (1D) . SNV andive (1D) . A wavelive (1D) . OSC canive (1D) . Normaliive (1D) .Ophiopogon japonicus with chemometrics. PLSR, SVM and SIMCA were selected as pattern recognition methods to study the effects of different spectral pretreatment methods on classification performance and to build the best model for origin tracing.Near-infrared spectroscopy combined with chemometrics analysis is an effective means of origin tracing, which has been confirmed by many studies. However, the existing research basically selects a single pretreatment method combined with a chemometric analysis method to build the origin tracing model. If the sample size is small, the establishment of a single model may reach a high or even 100% accuracy, but if the sample size is large, the accuracy of origin tracing may be slightly lower, with space for improvement. Therefore, choosing the best pretreatment method and suitable chemometrics method is particularly important. Based on the comparison of traditional single pretreatment methods, the best single pretreatment method was selected according to the results, combined with other effective methods to construct a combined pretreatment method, and used to assess the protected geographical indication of Zhejiang and non-Zhejiang Ophiopogon japonicus were relatively small, and there would have been optical path loss if it had been placed on the near-infrared spectrometer optical fiber alone, so a cylindrical open quartz bottle with a diameter of 35 mm at the bottom and a height of 20 mm was customized. The quartz bottle was filled with Ophiopogon japonicus, and then placed on the optical fiber of the near-infrared spectrometer for detection. The original NIR spectra of Ophiopogon japonicus from different habitats showed very similar diffuse reflection patterns in the range of 4000–12,000 cm−1. Ophiopogon japonicus.NIR spectra were obtained by near-infrared spectrometer . Near-infrared spectroscopy can be used for nondestructive testing, and the sample does not need to be cut or crushed. The samples of −1 are the combination regions of stretching vibration and bending vibration of CH and CH2, respectively. 5620–5885 and 5680–6060 cm−1 are the first overtone regions of CH and CH2, respectively. Similarly, 6855–7020 and 7010–7288 cm−1 are their second overtone regions. The second overtone region of C=O stretching vibration appears at 5230–5370 cm−1. All absorption peaks may be caused by the steroid saponins, high isoflavones and polysaccharides in Ophiopogon japonicus. As can be seen from Ophiopogon japonicus were consistent, which could not be distinguished by the naked eye.It can be seen from Ophiopogon japonicus after nine kinds of pretreatment are shown in Each NIR spectrogram has 2074 data points, and there are 3657 spectra, totaling 7,584,618 data points. The amount of data is very large and contains a lot of redundant information. Therefore, it is an effective method to select chemometrics to extract useful information from the spectra. The NIR spectra of Zhejiang and non-Zhejiang 2 statistic) and residuals in the spectral data. In both cases, high-value samples with a significant level of 5% were considered as outliers [Ophiopogon japonicus are shown in In this paper, PCA was chosen for outlier detection, and outliers were assessed by analyzing the high leverage  and the root mean square error (RMSE). The closer R2 is to 1, the better the prediction performance of the model is. R2 is greater than 0.91, indicating that the model meets the requirements. RMSE is used to calibrate, cross-validate, and predict during the analysis and evaluation of regression fit. The lower the RMSE value, the better the model prediction effect [Ophiopogon japonicus were divided into the training and test sets according to a 3:7 ratio using Monte Carlo cross validation (MCCV). Ophiopogon japonicus. Y is the dependent variable in PLSR analysis, representing the absorption obtained after near-infrared spectrum detection. The R2 and RMSE of the raw NIR spectra of Ophiopogon japonicus reached 0.995791 and 0.015651, respectively, indicating that the origin model of Ophiopogon japonicus was ideal and the prediction accuracy was high. It can be seen from 2 and RMSE are almost the same, which also explains the stability of the PLSR model.The evaluation of the PLSR system depends on the following two important indicators: the coefficient of determination  was used to model r and g represent SIMCA models of samples within the origin and outside the origin, respectively. D represents the distance between r and g, and k represents the variable. p is the number of data matrices.Ophiopogon japonicus, where SNV-T and SNV-F represent the distance between SIMCA models of Zhejiang and non-Zhejiang Ophiopogon, respectively, after SNV pretreatment. Similarly, MSC-T and MSC-F were the same. The distance between SIMCA-SNV-T and SIMCA-SNV-F was 5.5, while the distance between SIMCA-MSC-T and SIMCA-MSC-F was 4.5. The distances between both the two classification models of SIMCA-SNV and SIMCA-MSC were all greater than 3, indicating that the models have good performance and can be correctly classified.In order to verify the performance of the model established by SNV and MSC combined with SIMCA, distance graphs between the models were used for validation. According to Shirzadifar et al., the formula of the SIMCA model distance is as follows:t sample . Figure Ophiopogonis japonicum samples were collected from Zhejiang province, including 900 samples from Andong town of Cixi, 552 from Xinpu town of Cixi and 675 from Sanmen county of Taizhou. 1530 non-Zhejiang Ophiopogonis japonicum samples were collected from Sichuan, Hubei, Anhui and Shandong provinces, among which 765 were from Sichuan, 315 from Hubei, 225 from Anhui and 225 from Shandong. The Ophiopogon japonicus samples were put into a medicine washing machine, ultra-pure water was added so that Ophiopogon japonicus was submerged in water, and the machine was operated twice according to the standard operating procedures of the machine. The washed Ophiopogon japonicus samples were placed into an oven for dehydration, and were dried at 35 °C for 48 h. After washing and drying, all samples of Ophiopogonis japonicum were divided into the Zhejiang and non-Zhejiang categories.A total of 2127 Ophiopogon japonicus were collected by a Bruker Tensor 37 spectrometer in diffuse reflection mode. The samples were illuminated using a fiber optic bundle and scattered light was collected. The wave number of the original NIR spectrum ranged from 12,000 to 4000 cm−1. In the test conditions, the resolution and scanning times were 8 cm−1 and 64 cm−1, respectively.The NIR spectra of Abnormal values refer to sample points that deviate significantly from other data in the sample, also known as outliers. For the class model, outliers in the training set could lead to model bias and affect the accuracy of modeling . NIR speOphiopogon japonicus.In addition to the required basic sample characteristics, the spectral information collected by NIR spectrometer is often mixed with some irrelevant information, such as stray light and noise, which affects the accuracy of the modelling. Spectral preprocessing has the advantages of enhancing model representativeness and prediction ability, reducing random errors, ameliorating signal-to-noise ratio, resolving overlapping peaks, filtering out irrelevant information, and improving sensitivity. In this paper, nine pretreatment methods including mean centralization, area normalization, 1D, 2D, S-G smoothing, MSC, SNV, OSC and baseline correction were selected for spectral preprocessing of Zhejiang and non-Zhejiang 0 be N × m-dimensional data and Y0 be N × n-dimensional data. Let the first principal component axis vectors of X and Y be ω1 and C1, respectively, and the first pair of principal components t1 of X and u1 of Y be represented by ω1 and C1, where t1 = X × ω1, and u1 = Y × C1. The PLSR idea can be mathematically formalized as follows: maximize<Xω1, YC1>, subject to: Partial least squares regression (PLSR) has been widely used in quantitative and qualitative analyses of NIR spectroscopy. The PLSR algorithm is a statistical method that uses latent variable modeling to observe the relationship between variable sets. PLSR is especially applicable in cases where there are more prediction matrices than observed variables and with the presence of multicollinearity in X values . Let thereliable .The support vector machine (SVM) is an algorithm developed on the basis of statistical learning theory to solve machine learning problems. It has the advantage of high flexibility and can handle a large number of samples. SVM are widely used to solve regression problems and can create robust analysis models to effectively reduce the influence of outliers . The bask vector of the class q is represented by the PCA model of the class, and the unknown sample P is fitted. Then the similarity between the unknown sample P and the class q model is represented by fitting residual. The population deviation and fitting residual of the class q model are used to calculate the critical value, and the classification of unknown samples is judged based on this [Soft independent modeling of class analogies (SIMCA) is a pattern recognition method based on PCA. The classification of the whole sample is obtained after PCA analysis of the sample. On this basis, the corresponding class model of each sample is established, and then the unknown samples are reclassified according to the model, that is, the unknown samples are fitted with the class models of all samples respectively to determine the category . The k v on this .Ophiopogon japonicus. The effects of different spectral preprocessing methods on different pattern recognition methods were not the same after the removal of outliers. By comparing the RMSE and R2 of nine spectral preprocessing methods, it can be determined that SNV, MSC, OSC, first derivative, area normalization and baseline correction combined with PLSR can improve the prediction accuracy of the NIR tracing model, while second derivative, S-G smoothing and mean centering reduce the prediction accuracy. After selecting the combined pretreatment, the prediction accuracy of the PLSR model was significantly improved, but the model of SNV effect was still the best. After pretreatment with baseline correction, SNV, MSC and mean centering, the accuracy of the training and test sets of SVM was significantly improved, and reached the highest in SNV , while the other five pretreatment methods failed to reach the ideal state. Therefore, on the basis of SNV, combined with other preprocessing methods, according to the results, the SNV + S-G smoothing model, the SNV + detrending model, and the SNV + first derivative + S-G smoothing model each have relatively high accuracy on the training set and test set, and the SNV model still has the best effect. Both the PLSR and SVM models show that the combined preprocessing method can improve the accuracy of the training set and test set, but it is not necessarily the best choice. It may be that too many pretreatment methods leads to an overfitting of the model. For the SIMCA model, among the nine pretreatment methods, only SNV and MSC could achieve 100% accuracy for both the training set and test set, which may be the best method for tracing the origin of Ophiopogon japonicus. The distance between SIMCA-SNV-T and SIMCA-SNV-F models was greater than three, indicating that the model has good performance and could be correctly classified, where T and F represent Zhejiang and non-Zhejiang Ophiopogon japonicus, respectively. The distance between the SIMCA-MSC models also illuminated that SIMCA could effectively distinguish Zhejiang and non-Zhejiang Ophiopogon japonicus after MSC pretreatment.NIR spectroscopy combined with chemometric analysis can be effective for tracing the origin of To sum up, this paper believes that NIR-SNV-SIMCA is a highly accurate origin tracing model, which is applicable to food, medicine and other fields. SNV is widely used in the pretreatment of solid and liquid samples, especially for non-uniform samples, and has universal applicability. According to the characteristics of the sample, different kinds of spectral pretreatment methods can also be selected, or different effects of pretreatment methods combined with chemometrics can be used to build an accurate and efficient origin tracing model.