Navicula minima, decreased in the stream in 2013 and 2014 and increased in 2015 when precipitation and precipitation frequency were low. This was not clearly distinguishable in the ecological characteristics of each watercourse’s indicator species, except in SS. The dynamic community index was highest in 2015 (ca. 5.50), and the annual changes in the index were clearly shown in SS. The precipitation pattern and the dynamic community index were negatively correlated (r = −0.026~−0.385), and the precipitation within 2 weeks (r = −0.480 for SS) before the second sampling and the frequency of 10 mm of precipitation were closely correlated in the stream (r = −0.450 for SS). The distribution of epilithic diatoms in the four watercourses is therefore affected by monsoon precipitation and precipitation frequency, and the dynamic community index is determined by soil characteristics and land use.To study the effect of rainfall patterns on diatom communities in four major central western streams on the Korean Peninsula during the monsoon seasons of 2013 through 2015, we measured precipitation, environmental factors, and epilithic diatoms at 42 sites before (May) and after (August and September) each monsoon. The Mangyeonggang river and Sapgyocheon stream (SS) had a high percentage of low-permeability soil, and the stream had the highest proportion (49.1%) of surrounding land in urban areas. Precipitation and precipitation frequency was closely correlated with electrical conductivity and nutrients, and this was particularly evident in SS. Epilithic diatom abundance for the most abundant species as,  A monsoon is a seasonal weather phenomenon in which wind direction changes due to a temperature difference between the continent and the surrounding ocean . South KThe Geumgang River, Mangyeonggang River, Dongjingang River, and Sapgyocheon stream are classified as major watercourses that flow westward in the mid-western region of the Korean Peninsula ,10. PopuRainfall can change a river’s physiochemical characteristics, such as flow rate, flow velocity, turbidity, and nutritional substances ,17,18, aStudies have been conducted that monsoon affects changes in water quality and fish species on the Korean Peninsula ,32,33,34The present study describes the effect of rainfall patterns during the monsoon period on epilithic diatom communities. Environmental factors and epilithic diatoms in the Geumgang River, Mangyeonggang River, Dongjingang River, and Sapgyocheon stream in the mid-western region of the Korean Peninsula were surveyed before and after monsoons in 2013, 2014, and 2015.The Geumgang River (GR) is one of three major rivers in South Korea. Its main channel is 395.9 km long, flowing to the Yellow Sea via Daejeon, Sejong, and Nonsan. It has 31 tributaries, including the Bocheong-Cheon, Namdae-Cheon, and Gap-Cheon. The Mangyeonggang River (MR) and Dongjingang River (DR), which are in the south of the mid-western watershed, are mid-sized rivers that are joined by many tributaries and flow into the western sea across the Honam Plains. Around the Sapgyocheon stream (SS) in the north, a wide alluvial land, which is the sedimentary terrain of the river, has developed, and small and mid-sized cities and industrial complexes have been built around the stream. In the mid- to downstream reaches, agricultural land is leading ,39,40,41From 2013 to 2015, a survey was conducted at 42 sites on 4 major rivers in the mid-western region of the Korean Peninsula: 10 sites on the GR, 9 on the MR, 11 on the DR, and 12 on SS . The surTo identify the rainfall pattern in major rivers in the mid-western region of the Korean Peninsula due to the influence of monsoons, a water environment information system was used . The raiThe field survey table, including river width, water depth, and land use, identified the topography and river characteristics of the survey sites. To create the land use map around the survey sites for each river, a radius of 50 m from the sampling place was divided into urban, forest, agriculture, industrial complex, and livestock categories. To identify the soil characteristics in the survey sites, a radius of 50 m from the sampling place was categorized into A, B, C, and D classes  based on3-N), nitrate nitrogen (NO3-N), total phosphorus (TP), and phosphorus phosphate (PO4-P), the water in the site was sampled in a sterile 2 L water sampling bottle and transported to a laboratory in cold and dark conditions. Measurements of TN, NH3-N, NO3-N, TP, and PO4-P were taken using cadmium reduction, colorimetry, cadmium reduction, the ascorbic acid method after persulfate decomposition, and the ascorbic acid method, respectively [To investigate the water quality in the survey sites, water temperature, dissolved oxygen (DO), pH, electrical conductivity, and turbidity were directly measured in the field using the Horiba U-50 mobile water quality meter. In order to measure biological oxygen demand (BOD), a 300 mL sample of water collected at each site was put into a Winkler bottle and moved to a laboratory in cold and dark conditions and then incubated for five days at 20°C under a light-blocking condition according to Winkler’s azide method. BOD was the difference between the amount of consumed dissolved oxygen (DO) and the measured concentration of DO at the site. In order to analyze the water quality of total nitrogen (TN), ammonia nitrogen (NHectively .2) of the sampled substrate, and the samples were then cleansed with 200 mL of distilled water, fixed in Lugol’s solution, and transported to the laboratory. Permanent samples for taxonomic identification of the diatoms were prepared using a Naphrax encapsulant  after acid treatment and washing with a KMnO4 catalyst using the permanganate method [To collect epilithic diatoms, a site with flowing water that was submerged for more than three to four weeks was chosen. Wide and flat natural rocks whose upper side and water flow were in the same direction were selected. A soft brush was used to scrub diatoms from the upper part  was conducted . The indi: the distance between two communities with different times at the specific site in the PCA dimension. xi, yi: the first sampling site in PCA dimension before monsoon. xi′, yi′: the second sampling site in the PCA dimension after the monsoon.i: the distance between two communities with different times at the specific site in the PCA dimension. n: the number of sampling sites or communities.A dynamic community index (CDI) was calculated to identify community variation of epilithic diatoms due to rainfall. Principal component analysis (PCA) was conducted, and the distribution of each site was drawn in a two-dimensional space. The average community variation was calculated by computing the distance between the first and second surveys at each site .(1)di=xt-test. A Pearson correlation analysis and SPSS software were used to identify correlations between rainfall patterns, environmental factors, and epilithic diatom communities. In other statistical analyzes, data were converted into log10 values to increase the accuracy of the analysis by reducing the variation of epilithic diatoms and environmental factors. To prevent an error in log values when data with a value of 0 were converted, 1 was added to each variable to calculate Log10 (n + 1). PC-ORD software was used to calculate the CDI.In order to compare the physical-chemical environmental and biological factors  and community indexes between the groups, analysis of variance (ANOVA) was applied. Differences in the rivers before and after the monsoon were subjected to a The rainfall amount during the monsoon period was the largest in 2013 and the lowest in 2015 in all rivers . The raiThe rainfall frequency over a certain intensity during the monsoon period was counted. The frequency of 10 mm or more of precipitation was the highest in 2013 and the lowest in 2015 in the Geumgang River, but the frequency of rainfall of at least 30 mm was the highest in 2014. For the Mangyeonggang River and Dongjingang River, the frequency of rainfall ≥10 mm was the highest in 2014. The frequency of rainfall ≥30 mm was highest in 2013 and the lowest in 2015, similar to the rainfall pattern for the monsoon period. For the Sapgyocheon stream, the frequencies of rainfall of all intensities were the highest in 2013 and the lowest in 2015. Both the rainfall amount and frequency in the Sapgyocheon stream were the highest in 2013 and the lowest in 2015, as was the case with the rainfall patterns during the monsoon period.p < 0.01), while the proportion devoted to urban development was relatively high in the Sapgyocheon stream at 54.6% . In the Mangyeonggang River, the proportions of urban and forested areas were high at 44.1% and 23.5% , respectively. Land use around the rivers had a significant impact on water quality [The land use map showed a distinctive difference from river to river . The pro quality . Nutrien quality . However quality . In part quality .p < 0.01). Soil characteristic is an important factor in analyzing runoff due to rainfall. For example, Class D soil causes relatively higher runoff [Soil characteristics by the rivers were also surveyed . There wr runoff .p < 0.01). Before the monsoon, the Sapgyocheon stream had clearly higher DO levels (8.2 mg/L to 6.9 mg/L) compared with that of the Geumgang (7.3 mg/L to 7.8 mg/L), Mangyeonggang (7.3 mg/L to 7.9 mg/L), and Dongjingang (7.7 mg/L to 8.3 mg/L) rivers . After the monsoons, DO was significantly reduced in the Sapgyocheon stream, reaching its lowest value .The environmental factors in the four studied rivers showed distinctive differences before and after monsoons . The watp < 0.05). It increased in all rivers after monsoons.Electrical conductivity increased in all rivers before and after monsoons, but it varied from river to river. Electrical conductivity was relatively low in the Geumgang River  and the Dongjingang River , whereas it was relatively high in the Mangyeonggang River  and Sapgyocheon stream  , but no significant difference was seen in the Geumgang River , Mangyeonggang River , and Dongjingang River . TN levels decreased in all rivers after the monsoon, particularly in the Sapgyocheon stream . NH3-N was also the highest in the Sapgyocheon stream  before and after the monsoons, whereas no significant difference was found in the Geumgang River , Mangyeonggang River , and Dongjingang River . TP levels before the monsoon were the highest in the Sapgyocheon stream, and no significant change was found in any rivers before and after the monsoon.Turbidity levels decreased in all rivers and were the highest in the Geumgang River  before and after the monsoon. TN levels were the highest in the Sapgyocheon stream  before and after the monsoon . The DO variation showed a correlation only in the Mangyeonggang River and Sapgyocheon stream , and pH showed a negative correlation only in the Dongjin River . Variation in electrical conductivity was negatively correlated with rainfall amount in the Geumgang River and Dongjingang River before sampling but positively correlated with that of the Mangyeonggang River and Sapgyocheon stream. The Mangyeonggang River and Sapgyocheon stream had many D-class soils with low permeability that exhibited high runoff during rainfall events [3-N and TP showed a significant correlation with rainfall before the second sampling in the Mangyeonggang River and Sapgyocheon stream. A negative correlation was evident in the Mangyeonggang River, and a positive correlation was revealed in the Sapgyocheon stream. The Sapgyocheon stream had a high proportion of urban areas with high pollution levels and rich nutrients. Urban areas have large areas of impermeable surfaces and high rainwater runoff during rainfalls, which supplies fine sediment and pollutants to the rivers [l events . Becausee rivers ,58. ThisThe epilithic diatoms that appeared for three years in the rivers in the mid-western region of the Korean Peninsula represented 222 taxa consisting of 2 orders, 3 suborders, 9 families, 37 genera, 200 species, 19 varieties, 2 forma, and 1 subspecies. The variation of major species in each water system before and after the monsoon is as follows .Melosira varians C. Agardh, Navicula minima Grunow, and Aulacoseira granulata (Ehrenberg) Simonsen, were found. The highest-standing crops were Melosira varians and Nitzschia palea (Kützing) W. Smith before monsoons and Aulacoseira granulata and Melosira varians after monsoons. The standing crop of Melosira varians, which was high throughout the survey period, occurred primarily in eutrophic waters [Navicula minima, Aulacoseira granulate, and Cyclotella meneghiniana Kützing increased after the monsoons.Geumgang River: Five major species, including c waters . The staNitzchia palea, Melosira varians, and Fragilaria elliptica Schumann, were found. The highest-standing crops were Melosira varians and Nitzchia palea before the monsoons and Nitzchia palea and Fragilaria elliptica after the monsoons. Nitzchia palea, which was a high-standing crop throughout the survey period, was an indifferent species. It was resistant to pollution and appeared as a dominant species in polluted waters [Nitzchia palea and Melosira varians increased in 2013, and the standing crop of Melosira varians increased in 2014. In 2015, the populations of Melosira varians and Fragilaria elliptica, which were floating species, increased significantly.Mangyeonggang River: Three major species, d waters . The staNitzchia palea, Melosira varians, and Nitzchia amphibia Grunow, were found. The highest-standing crops were Nitzchia palea and Melosira varians before the monsoons and Nitzschia palea and Nitzschia amphibia after the monsoons. The standing crop of Nitzschia palea increased in 2013, and the most standing crops decreased in 2014. The proportion of Nitzschia amphibia significantly increased in 2015. It is known as an indifferent species and often appears in nutrient-rich waters [Dongjingang River: Five major species, including h waters .Navicula minima, Nitzchia palea, and Gomphonema lagenula Kützing appeared. The highest-standing crops were Nitzchia palea and Navicula minima before and after the monsoons. Nitzchia palea is known to appear in nutrient-rich waters as a dominant species [Navicula minima are known to grow in a wide range from freshwater to weak brackish water. The standing crops of major species decreased in 2013 and 2014, and most standing crops distinctively increased in 2015. Most standing crops of the major species in the Sapgyocheon stream significantly decreased after the monsoons of 2013 and 2014 and increased in 2015. In 2013 and 2014, when the rainfall amount and frequency were relatively large, the standing crop of epilithic diatoms decreased after the monsoons. This was the result of the ease of detachment of epilithic diatoms caused by the flow that occurred during rainfall and erosion by suspended sediment [Sapgyocheon stream: Six major species, including  species , and Navsediment . HoweverTo identify epilithic diatoms that can represent variable environments along with rainfall on the rivers in the mid-western region of the Korean Peninsula, ISA was performed on each group’s biological community :Navicula capitatoradiata H. Germain ex Gasse and Achnanthes hungarica (Grunow) Grunow in 2013, Navicula veneta Kützing in 2014, and four species including Cyclotella stelligera (Cleve & Grunow) Van Heurck and Navicula cryptotenella Lange-Bertalot in 2015  Kützing and Aulacoseira ambigua (Grunow) Simonsen in 2013, three species, including Navicula veneta and Navicula amphiceropsis Lange-Bertalot & U. Rumrich in 2014, and Aulacoseira granulata var. angustissima (O. Müller) Simonsen and Navicula schroeteri F. Meister in 2015. Gomphonema parvulum, which was dominant in 2013, appeared in eutrophic water bodies where there was considerable sewage inflow [Navicula veneta, which was the same indicator species before the monsoon, appeared with a high indicator value after the monsoon in 2014. Aulacoseira granulata var. angustissima, which was an indifferent species, appeared in 2015. The species that appeared in the Geumgang River before the monsoons showed a high indicator value in indifferent species. Saproxenous species appeared after the monsoon in 2013, when the rainfall amount and frequency were large, and the same species appeared in 2014 before and after the monsoon. Indifferent species appeared after the monsoon in 2015.Geumgang River: Five indicator species were identified before the monsoon, including  in 2015 . Naviculeshwater . Naviculc waters . Naviculed areas . The inde inflow . NaviculFragilaria bidens Heiberg and Gomphonema pseudoaugur Lange-Bertalot and Navicula viridula var. rostellata (Kützing), Cleve and Navicula trivialis Lange-Bertalot were identified in 2014, followed by Fragilaria capucina Desmazières, Cyclotella stelligera, and Surirella angusta Kützing in 2015  Van Heurck and Navicula gregaria Donkin were identified in 2014, followed by Cymbella leptoceros (Ehrenberg) Kützing and Navicula decussis Østrup in 2015. Cymbella affinis, which appeared in 2013, is known to prefer waters with average levels of electrolytes [Cocconeis placentula var. lineata, which appeared in 2014, is often found in mesotrophic and eutrophic waters [Cymbella leptoceros, which appeared in 2015, is known to prefer mesotrophic waters [Mangyeonggang River: Three indicator species were identified before the monsoon in 2013, including  in 2015 . Fragilakalinity ,64. Thretrolytes . Cocconec waters . Cymbellc waters . SpeciesCocconeis placentula var. lineata and Aulacoseira ambigua in 2013. Six species, including Gomphonema parvulum and Fragilaria bidens, appeared in 2014, and Cyclotella atomus Hustedt was found in 2015  Lange-Bertalot and Navicula notha J.H. Wallace, appeared in 2013 as indicator species after the monsoons. An indicator species in 2014, Fragilaria delicatissima Proshkina-Lavrenko, did not appear in 2015. Navicula recens, which appeared in 2013, is an indifferent species that is widely distributed in eutrophic rivers with high electrical conductivity [Fragilaria delicatissima, which appeared in 2014, is known to prefer a neutral pH and is indifferent to organic pollutants [Dongjingang River: Eight indicator species appeared before the monsoon, including  in 2015 . Cocconec rivers . Six speuctivity . Fragilallutants . SpeciesNavicula cari Ehrenberg and Fragilaria bidens in 2013, Navicula cryptocephala Kützing in 2014, and Fragilaria elliptica and Navicula veneta in 2015  Grunow and Cyclotella stelligera appeared. In particular, Cyclotella stelligera is known to prefer oligotrophic or mesotrophic waters [Sapgyocheon stream: Indicator species before the monsoons were  in 2015 . Naviculuctivity ,66. Naviuctivity . As an ic waters . In the In summary, the ecological characteristics of the indicator species that appeared in the Geumgang River, Mangyeonggang River, and Dongjingang River before and after the monsoon were not distinctively different. In the Sapgyocheon stream, saproxenous species that preferred eutrophic waters appeared before the monsoons each year, and after the monsoons, saproxenous species appeared in 2013. In 2015, when the rainfall amount and frequency were low, species that preferred mesotrophic waters appeared, indicating that the ecological characteristics of the indicator species were distinctively differentiated according to the rainfall pattern.To identify the distribution of epilithic diatoms before and after the monsoon, PCA was conducted using the number of species that appeared for three years and the standing crop of each species. The analysis revealed that the epilithic diatom community could be divided by survey period. Before the monsoon in 2013, diatoms were distributed in the positive direction along axis 1, with a similar trend evident after the monsoon. The diatoms were distributed in both positive and negative directions before and after the monsoons in 2014. In 2015, they were distributed in the negative region along axis 2 a. To quap < 0.01). Rainfalls cause an influx of nutrients from urban and agricultural areas to the rivers [The results of the analysis of the CDI in each river showed that the highest CDI (ca. 5.50) occurred in 2015 when the rainfall amount and frequency were small in all rivers c. The Sae rivers ,69, and e rivers ,70. The In a study by Cho et al. (2020) , the varIn conclusion, the largest change in the epilithic diatom community occurred in 2015, when the habitat environment changed distinctively due to a small amount of rainfall, and the Sapgyocheon stream experienced significant yearly changes because of the large number of urban impermeable surfaces and low-permeability soils.p < 0.05). The sum of rainfalls for one and two weeks in the second survey and the rainfall amount during the monsoon periods showed a significant correlation with the CDI in the Sapgyocheon stream, and the rainfall amount within two weeks had the highest correlation (p < 0.01).The relationship between community variation and rainfall showed a mainly negative correlation, with a significant correlation seen in the Mangyeonggang River and Sapgyocheon stream . Sapgyocp < 0.01).The CDI and rainfall frequency also showed a primarily negative correlation, with a significant correlation seen in the Mangyeonggang River and Sapgyocheon stream. The frequency of rainfall events ≥30 mm and ≥50 mm influenced the CDI in the Mangyeonggang River. The highest correlation was with the intensity and frequency of rainfall ≥30 mm. In the Sapgyocheon stream, the frequency of rainfall ≥10 mm, ≥30 mm, ≥50 mm, and ≥70 mm exhibited a correlation, and the frequency of rainfall ≥10 mm had the highest correlation with the CDI  in the monsoon period. In addition, the epilithic diatom community variation was also closely correlated with land use and soil characteristics around the surveyed rivers. Finally, the community variation was larger as the rainfall amount and frequency (intensity) were lower in the Sapgyocheon stream, which exhibited low permeability and high nutrient concentrations.


Polycystic ovary syndrome (PCOS) is one of the most common endocrine disorders in females characterized by ovulatory dysfunction, hyperandrogenism, and other metabolic disorders. Both intermittent fasting and specific probiotics have been suggested to help improve patients with PCOS through changes in gut microbial composition, circadian clock, and metabolic regulation. Therefore, the present study aims to investigate the effects of intermittent fasting alone or in combination with probiotic supplementation compared to the calorie-restricted (CR) diet on anthropometric measures, metabolic status, inflammation, and oxidative stress in women with PCOS.n = 30); (2) a 14:10 early TRF diet with placebo supplementation (n = 30); (3) a CR diet  with placebo supplementation as a control group (n = 30). The primary outcomes will be changes in body weight and insulin resistance. However, glycemic control, lipid profile, metabolic parameters, sex hormone-binding globulin, dehydroepiandrosterone, anti-Mullerian hormone, free androgen index, hirsutism, acne, antioxidant and oxidant status, inflammation, anthropometric measures, mental health, sleep quality, appetite, eating behavior, food craving, and blood pressure are secondary outcomes. All outcomes of this study will be evaluated in pre- and post-intervention.We will carry out a randomized clinical trial for 8 weeks. Participants will be randomly assigned (1:1:1) to one of the three groups: (1) a 14:10 early time-restricted feeding (TRF) diet with probiotic supplementation .Iranian Registry of Clinical Trials IRCT20121110011421N5. Registered on 3 October 2022.The online version contains supplementary material available at 10.1186/s13063-023-07691-5. Polycystic ovary syndrome (PCOS), one of the most common endocrine disorders in females, approximately affects 7 to 12% of women of reproductive age .Recently, dietary interventions have been taken into consideration for the management of PCOS. Because up to 60% of PCOS women are overweight or obese, evidence-based international guidelines emphasize the importance of diet and recommend dietary and exercise interventions as the first line of management for this disorder . To dateIntermittent fasting (IF) is a promising alternative, which has been shown to improve cardiometabolic status while adhering to weight loss goals . IF is tLactobacillus and Bifidobacterium have been proposed as the most effective species for regulating sex hormones and metabolic parameters  ; Depressα = 0.05), a power of 80%, according to the mean weight loss of 2.5 kg  as the principal outcome and the standard deviation of 3.87 and 3.04 [By consideration of a type I error of 5%  will be used for recording participant data. Data entry and management will be done using an electronic database after CRFs are used for data collection. There will be two data collectors, and completed clinical raw data will be sent for approval to the project supervisor. Documentation is kept in a locked drawer, only accessible by the principal investigator. The forms contain an ID number unique to the participant and do not contain any information that can be used to identify the patient.A clinical trial monitor occasionally supervises the study progress and ensures patient rights and well-being are safeguarded; the protocol, ethical requirements, standards, and regulations are being followed; the essential documentation is available; and collected data are accurate as there were recorded. One of the investigators will check the coding, security, and storage of data. In addition, she will evaluate data entry and data values twice. If any participant reports the occurrence of adverse events, more information is required to make a decision about excluding the participants from the trial. Unblinding is permissible in this situation based on the Medical Ethics Committee criteria. Ethical review of the data will be overseen by the Tehran University of Medical Sciences. Further, patients who discontinue the study or deviate from it will be provided with a list of all outcome data. Missing data will be imputed using modern methods for dropouts.Participants are at minimal risk during the intervention and measurement protocols. Since this trial is low-risk, close monitoring by the principal investigator and an independent Safety Officer is part of the data safety monitoring plan. Any adverse event that exceeds the threshold and any serious adverse event will be promptly reported to the NIH and the COMIRB by the principal investigator and an independent Safety Officer. During the annual Safety Officer meeting, the Safety Officer will review the study coordinator’s reports to determine if any corrective action, trigger for an ad hoc review, or stopping rule violation should be reported to the study investigators, the COMIRB, and the sponsor.t-test and Mann–Whitney U test will be applied to compare continuous variables between-group, whereas we will use paired sample t-test and Wilcoxon rank-sum test for within-group comparisons. To compare the differences in primary and secondary outcomes between the two study groups at the end of the trial and adjust the final findings for potential confounders, we will apply the mixed linear effect model. To correct for multiple comparisons and reduce alpha error, q values will be used using the Benjamin-Hochberg method. Based on this, significance was defined in P values less than 0.05 and q values less than 0.1. Cohen’s d will be calculated based on the mean and standard deviation. The effect sizes 0.20, 0.50, and 0.80, respectively for low, medium, and high therapeutic effects of the dietary intervention will be determined. No subgroup analyses are planned. However, no interim analyses are planned for this trial.All analyses will be performed according to the Intention to Treat Analysis (ITT) method. Therefore, all participants who entered the study (regardless of whether they completed the 8-week study period) are included in the analysis. Missing data will be checked by multiple imputations. Statistical analysis will be conducted using the SPSS software . The scatter diagram, histogram, and Kolmogorov–Smirnov test will be applied to examine the normality of the data. Normally distributed variables will be reported as the mean and standard deviation, while the median and interquartile range (IQR) will be used for reporting non-normally distributed variables. Moreover, we will use the chi-square test and Fisher’s exact test to compare categorical variables. Also, the independent sample When participants sign the consent form, they will be asked if they consent to their data being used in the event of withdrawal. Also, researchers will ask participants for permission to share relevant data with people from the participating universities or regulatory authorities. Biological specimens are not collected for storage in this trial.PCOS is a complex endocrine disorder characterized by ovulatory dysfunction, hyperandrogenism, and other metabolic disorders . DisturbLactobacillus rhamnosus supplementation enhanced the effectiveness of weight loss therapy for obese women, as demonstrated by Hulston et al. [Lactobacillus reuteri was shown to improve glucose tolerance in rats with constant darkness-induced PCOS in a previous study [Lactobacillus rhamnosus and roteri can play a positive role in restoring the vaginal microecology and treating bacterial vaginosis. So, correcting the microbial condition of the vagina by improving the menstrual cycle and AMH level leads to improvement in fertility [Patients with PCOS have significant changes in the composition of the gut microbiota. This change was associated with a decrease in α diversity and changes in β diversity . There in et al. . Also, Lus study . In addiertility . Probiotertility , 73.We hypothesized that 10-h TRE administered alone or in combination with probiotic supplementation to overweight and obese PCOS subjects would lead to weight loss and improved metabolic, hormonal, inflammatory, and antioxidant markers compared to control subjects following a standard 3-meal-per-day CR diet. To the best of our knowledge, no clinical trial has investigated the effect of IF diet combination with probiotics supplementation in patients with PCOS. Therefore, the present study aims to investigate the effects of IF alone or in combination with probiotic supplementation compared to the CR diet on anthropometric measures, metabolic status, inflammation, and oxidative stress in women with PCOS. If successful, nutritionists in clinical environments may recommend a new eating pattern (TRF) alone or along with probiotic supplements for patients with PCOS to treat this common disorder.Iranian Registry of Clinical Trials IRCT20121110011421N5. Registered on 3 October 2022. The recruitment started on 23 October 2022 and will be almost finished on 23 September 2023.Additional file 1. SPIRIT 2013 Checklist.


Stroke is a heavy burden in modern society, and carotid artery disease is a major cause. The role of the extracellular matrix (ECM) in the development and progression of carotid artery disease has become a popular research focus. However, there is no published bibliometric analysis to derive the main publication features and trends in this scientific area. We aim to conduct a bibliometric analysis to reveal current status of ECM in carotid artery disease and to predict future hot spots.We searched and downloaded articles from the Web of Science Core Collection with “Carotid” and “Extracellular Matrix” as subject words from 1990 to 2021. The complete bibliographic data were analyzed by Bibliometrics, BICOMB, gCLUTO and CiteSpace softwares.Since 1990, the United States has been the leader in the number of publications in the field of ECM in carotid artery disease, followed by China, Japan and Germany. Among institutions, Institut National De La Sante Et De La Recherche Medicale Inserm, University of Washington Seattle and Harvard University are in the top 3. “Arteriosclerosis Thrombosis and Vascular Biology” is the most popular journal and “Circulation” is the most cited journal. “Clowes AW”, “Hedin Ulf” and “Nilsson Jan” are the top three authors of published articles. Finally, we investigated the frontiers through the strongest citation bursts, conducted keyword biclustering analysis, and discovered five clusters of research hotspots. Our research provided a comprehensive analysis of the fundamental data, knowledge organization, and dynamic evolution of research about ECM in carotid artery disease.The field of ECM in carotid artery disease has received increasing attention. We summarized the history of the field and predicted five future hotspots through bibliometric analysis. This study provided a reference for researchers in this fields, and the methodology can be extended to other fields.The online version contains supplementary material available at 10.1186/s40001-023-01259-4. Stroke is one of the main causes of death and morbidity in our aging society, among which ischemic stroke accounts for 87% of all strokes . 13% to The formation of carotid artery disease is a chronic and long-term process. The microenvironment of artery wall plays important roles in the progress of the disease. ECM is the main component of vascular microenvironment, which is critical for the functional stability of blood vessels and closely related with the occurrence of ischemic stroke. About 300 proteins make up the matrisome, which is the center of the vascular ECM , 9, inclAlong with the recognition of the roles of ECM in the development of carotid artery disease, many striking research emerged in the past decades. Therefore, exploring new techniques for automated data analysis to extract useful knowledge is an exciting task. Bibliometric analysis has gained popularity in recent years, which measures the contribution of a research field and makes detailed predictions about the research trends or hotspots in a certain subject –17. HoweThe database: Web of Science Core collection, Edition: (SCI-EXPANDED) -1990- present. The search term was set as (TS = (Carotid)) AND TS = (Extracellular Matrix) and obtained 1191 literatures. Then, we set the document type as “article” and finally acquired 1056 articles. The relevant literature was first appeared in 1990. Thus, the time was set from 1990–01–01 to 2021–12–31, and 1041 articles were finally obtained. The above search results were completed on July 5, 2022.http://bibliometric.com/) and CiteSpace  for bibliometric analysis. In this analysis, we took publication factors including countries, organizations, journals, authors, and the H-index [Web of Science was used to retrieve the data that included full records and cited references. We used Bibliometrics  published the largest number of articles, followed by China 108), Japan (90), Germany (89), etc.  is the first stage of atherosclerosis , 30. TheCluster 2 relates to the ECM in stability of carotid atherosclerotic plaque. Atherosclerotic plaques are composed of lipids, ECM and several cell types, mainly including bone marrow-derived cells, VSMCs and endothelial cells . RuptureCluster 3 relates to correlation between ECM of carotid plaque and age. Age has been shown to be a major determinant for cross-sectional area of carotid artery , and carCluster 4 relates to ECM affects the mechanical properties of carotid artery. Carotid artery curvature is usually associated with aging, hypertension, atherosclerosis and degenerative vascular diseases, while the mechanism is still unclear –46. PrevWith the in-depth study of ECM, its importance in carotid artery disease has been further highlighted. Using ECM proteomics, Manuel et al. compared the ECM profiles of symptomatic and asymptomatic carotid plaques and identified four proteins, matrix metalloproteinase 9, S100 calcium binding protein A8/A9, cathepsin D, and galectin-3-binding protein. The above four proteins improved risk prediction and diagnosis in carotid artery disease management . MeanwhiIn interpreting the results of this study, several limitations should be noted. The databases are regularly updated, and we only included articles that were published between 1990 and 2021. Consequently, there may be a mismatch between our bibliometric analysis and actual publication circumstances. Future regular updates of the study to clarify the line of research on ECM in carotid artery disease are still needed.Through bibliometric analysis, we performed a comprehensive analysis of the knowledge organization of the underlying data for articles about ECM in carotid artery disease between 1990 and 2021. The past of the field is summarized, and future hotspots are predicted. These results can provide a useful reference for researchers in the field.Additional file 1. The top 10 countries/regions contributing to publications about ECM in carotid artery disease.Additional file 2. The top 10 institutions contributing to publications about ECM in carotid artery disease.Additional file 3. The top 10 most active journals that published articles about ECM in carotid artery disease.Additional file 4. The top 10 most productive authors contributed to publications about ECM in carotid artery disease.Additional file 5. The top 10 high-cited articles about ECM in carotid artery disease during 1990 to 2021.


Listeria monocytogenes and Salmonella enteritidis. The models developed in this study exhibited high prediction quality, as indicated by high r2 values during the training cycle. The best fit between the modeled and measured values was observed for the inhibition of adhesion. This study provides a valuable contribution to the field, supporting industrial settings during the initial stage of biofilm formation, when these communities are the most vulnerable, and promoting innovative and improved safety management.The problem of microbial biofilms has come to the fore alongside food, pharmaceutical, and healthcare industrialization. The development of new antibiofilm products has become urgent, but it includes bioprospecting and is time and money-consuming. Contemporary efforts are directed at the pursuit of effective compounds of natural origin, also known as “green” agents. Mushrooms appear to be a possible new source of antibiofilm compounds, as has been demonstrated recently. The existing modeling methods are directed toward predicting bacterial biofilm formation, not in the presence of antibiofilm materials. Moreover, the modeling is almost exclusively targeted at biofilms in healthcare, while modeling related to the food industry remains under-researched. The present study applied an Artificial Neural Network (ANN) model to analyze the anti-adhesion and anti-biofilm-forming effects of 40 extracts from 20 mushroom species against two very important food-borne bacterial species for food and food-related industries— L. monocytogenes found in Dole’s salad [L. monocytogenes outbreaks in the past because the biofilm this food-borne pathogen produces enables it to stick to processing equipment. Hudson Valley Farms recalled their nuts and nut butter products because of the same problem of Listeria biofilm [In December 2021 the Dole company from the USA recalled its iceberg lettuce and any finished products containing it. A Food and Drug Administration (FDA) and Center for Disease Control (CDC) investigation showed that 18 people from 13 states ended up infected with  biofilm . The foc biofilm . One out biofilm . The mos biofilm . However biofilm . There a biofilm ,11,12.Pleurotus flabellatus strain Mynuk, which expressed antiadhesion and antibiofilm activity against ATCC and the clinical isolates of several pathogens. Chlorinated orcinol derivate, a compound from the mycelial culture of North American Hericium sp. has been demonstrated as an effective agent in the prevention of pathogenic fungi biofilm formation [Plants are already well-known and traditionally used sources of antimicrobial and antibiofilm compounds. Different parts, such as leaf, root, fruit, or peel, are rich in antibiofilm compounds, as has been demonstrated recently using the simple and cheap crystal violet staining method . Recentlormation . One shoormation . Thus, mBoswellia sacra Flueck.) got to the clinical trial phase for periodontal diseases [As recently cited here, there are several promising compounds of natural origin, and only a scarce number of them have been tested in a clinical setting. According to the database of , only a diseases . This imdiseases . Shaban diseases  presenteThus, the goal of this study was to apply ANN as a good mathematical tool when there is a high variability of the variables and the nonlinear behavior of process parameters , which aIt should be of significant use in the industrial setting, such as food manufacturing, which cannot deal with time- and resources-consuming assays. The ANN model does not need physical model parameters, but still encompasses a capacity to obtain results from the experimental data and is able to handle the complex system with nonlinearities and to elaborate the interactions between variables ,30. Considering the aim of testing, a high number of different mushroom extracts was involved in antimicrobial and antibiofilm activity assays; the list of mushroom species, specific extracts, and their abbreviations are given in S. enteritidis, while the alkali extract of Meripilus giganteus and Ganoderma lucidum killed Gram-positive L. monocytogenes when the maximal tested concentration (20 mg/mL) was applied. In all cases, except one, the MIC of alkali-extracted samples was lower than the MIC of water extracts. In several cases, there was no difference concerning the method of extraction and antibacterial effect. The strongest inhibition of bacterial growth was recorded in the case of S. enteritidis and alkali extracts of Trametes versicolor and Picipes badius (2.5 mg/mL), while the water extract of Cratherellus cornucopioides had the lowest MIC against L. monocytogenes (2.5 mg/mL). Extracts derived from polypore species were not more effective than those extracted from the other groups.The majority of tested samples exhibited antimicrobial activity toward both strains of food-borne bacteria, with minimal inhibitory concentrations (MIC) being mainly in the range of 10–20 mg/mL . SpecifiL. monocytogenes, usually between 50 and 60% , so they expressed biofilm formation inhibition, while antiadhesion activity evolved; approximately 50% antibiofilm-forming effect went up to approximately 100%. Gram-positive bacteria were again slightly more sensitive. Alkali extracts (over 90% of samples) mostly had higher antibiofilm-forming activity, and the effect was concentration-dependent in the same manner as with the antiadhesion activity. The highest tested concentration was the least effective, or even had no effect, while the concentrations in the range of 0.312–0.625 mg/mL had the strongest antibiofilm-forming effect. Mushroom extracts were able to prevent both bacterial strains’ adhesion to a polystyrene surface. The effect was stronger against  and 60% . The typ2 value throughout the training cycle was obtained when the nine hidden neurons were used to build the ANN model  and results depend on the initial presumptions of the matrix parameters, which are vital for ANN building and fitting to experimental data. In addition, the number of neurons in the hidden layer can change the conduct of the ANN model. In order to avoid this issue, each topology was run 100,000 times to avoid random correlation due to initial assumption and random initialization of the weights. According to this approach, the highest rNN model a. The model was trained for 100 epochs, and the training results, i.e., train accuracy and error (loss), are presented in Fomitopsis pinicola possesses several compounds that strongly affect multidrug-resistant bacteria [Clitocybe geotropa, together with Lentinula edodes, had the highest antimicrobial activity against several tested pathogens. In this study, C. geotropa was among the least effective species (both types of extracts), which might be the consequence of the more aggressive extraction procedure applied here, which included high temperature and high pressure. In addition, alkali extraction is an efficient method for cell wall degradation, followed by the transformation of water-insoluble compounds [Escherichia coli efficiently act as antibiofilm agents toward other pathogenic strains. They are defined as the key competition compounds and are even autoregulatory [Marasmius oreades had a weak antimicrobial but a significant antibiofilm effect [The antibacterial activity of mushroom-derived compounds or mushroom extracts has been extensively explored and reported for more than two decades. It was a step towards the search for naturally derived antibiotics due to the ever-more present threat of bacterial resistance. As stated by the World Health Organization (WHO) and CDC, microbial resistance presents a global health, development, and economic threat ,32. Alvebacteria . The sambacteria . In the ompounds . Thus, tompounds . For exagulatory . Becausegulatory . Similarm effect .L. edodes extract samples, ranging from 20 to 30%, which is significantly lower than in the present study. They also established dose-dependent activity, although not in all cases. Lower doses when combined had additive outcomes, while higher doses acted antagonistically. The observed effect was attributed to the physicochemical interactions between the compounds in complex extracts. Kavita [Oceanobacillus iheyensis, noticing a dose-dependent relation up to a specific concentration of tested material. This was also observed in this study, and the cut-off value varied with different samples. In most cases, it was 0.312 or 0.625 mg/mL. Some of the species examined here have already been tested for their antibiofilm activity and reported by other authors, although the bacterial strains were not the same [B. edulis had high efficiency in removing the biofilms of Staphylococcus aureus and E. coli , which is in agreement with the findings reported here for water extract of the same fungi species against L. monocytogenes and S. enteritidis . In both studies, the antibiofilm effect of this popular edible mushroom was stronger against Gram-negative bacteria.The problem of bacterial biofilms is well-known in the food industry and is usually treated by chemical and physical methods, which are expensive, hard to perform, vary in stability and thus efficiency, contribute to microbial resistance, and can even jeopardize consumer’s health ,44. Espe. Kavita  discussethe same . Their aSeveral compounds might be responsible for the antibiofilm effect of mushrooms. Polysaccharides, proteins, peptides, and small water-soluble molecules, such as phenolic compounds, were identified as the responsible active agents . DiffereE. coli [In addition, the mushroom extracts tested in this study mostly did not express bactericidal activity, while at the same time demonstrating an antibiofilm-forming effect. Thus, the prospect of building microbial resistance is non-existent or unlikely, which makes this material highly interesting for practical application. Moreover, mushroom polysaccharide extracts are water-soluble and mainly non-toxic, which is not the case with some other highly efficient antibiofilm polysaccharides, such as the ones isolated from non-pathogenic E. coli .Although the predictive capabilities of the ANN modeling technique have been tested on different antimicrobial potential setups ,28,53,542), with an overall value of 0.856 for the training period, and low values of the sum of squares (SOS), as seen in The ANN model showed a good ability to generalize and predict experimental data. Based on its performance, the optimal number of neurons in the hidden layer for predicting the inhibition of adhesion and the inhibition of the biofilm-forming process was found to be 9 (MLP 25-9-2 network), resulting in high values of the coefficient of determination (rW1 and vector B1 (presented in the bias row), and W2 and vector B2 (bias) for the hidden layer, for the ANN model, which were calculated using Equation (2). The performance of the ANN model was evaluated by comparing its calculated outputs to the experimental measurements, represented as the sum of the coefficient of determination (r2) between measured and calculated values for the inhibition of adhesion and inhibition of the biofilm-forming process. The results showed that the goodness of fit was 0.894, 0.863, and 0.887 for the training, testing, and validation steps, respectively, for the inhibition of adhesion and 0.856, 0.796, and 0.781 for the inhibition of the biofilm-forming process. The ANN models were able to predict the experimental variables with good accuracy for a wide range of process variables, as seen in 2 value. This is in line with other studies in the literature that have reported similar results for the inhibition of adhesion and inhibition of biofilm-forming processes [2 value between the experimental and ANN model outputs was 0.865 for the inhibition of adhesion and inhibition of biofilm-forming processes.The ANN models were highly successful in predicting values that were very close to the desired values, as indicated by the high rrocesses ,56,57. Trocesses ,58. Duri2, MBE, RMSE, and MPE values [2 value indicates that the variation was accounted for and that the data fit satisfactorily to the proposed model [The quality of the ANN model fit was assessed using χE values , which sed model ,61.2 value [The predicted values were very close to the desired values in most cases, in terms of r2 value .2) value close to 1. Additionally, to achieve a good fit to the experimental values, it is desirable for the values of other tests, such as χ2, MBE, RMSE, and MPE, to be as low as possible [The fit of the model was evaluated using possible ,61.L. monocytogenes was found to have the greatest positive influence on the inhibition of adhesion, with a relative importance of approximately +8.72%. Conversely, the concentration of S. enteritidis, as well as the concentrations of extracts Fh and GI, were identified as the most negatively influential parameters on the inhibition of adhesion, with relative influences of −6.24%, −13.24%, and −10.81%, respectively.In this study, the relative influence of 25 input variables on the inhibition of adhesion and inhibition of the biofilm-forming process was analyzed. According to the results shown in L. monocytogenes, as well as extracts of mushrooms As, Dq, Fp, and Sc, with relative influences of +6.90%, +6.03%, +9.07%, +7.70%, and +7.76%, respectively. The most pronounced negative influence on the inhibition of the biofilm-forming process was observed for the Conc. and Tv mushroom extracts, with relative influences reaching −10.04% and −10.61%.For the inhibition of the biofilm-forming process, a positive influence was observed for the concentration of w/v), tryptic soy broth, 2,3,5-triphenyltetrazoliumchloride (TTC), and crystal violet solution (1%) were all obtained from Sigma Aldrich .Ethanol  according to the methods of classical herbarium taxonomy; the micro- and macromorphology of collected specimens were compared to standard descriptions in the taxonomic monographs. The representative voucher specimens, including their mycelial cultures, were deposited in the specimen collection of the Institute of Food Technology and Biochemistry, University of Belgrade—Faculty of Agriculture. To prepare them for extraction, mushroom samples were brush-cleaned and air-dried (40 °C) to constant mass. After being powdered in a Cyclotec mill , 40 mesh, the samples were stored in a cool and dark place prior to analysis.w/v) and mixed in a magnetic stirrer, filtered, mixed with water, and autoclaved for 1 h . After being cooled, the material was filtered through cotton wool, and the liquid part was evaporated on a hot plate magnetic stirrer until 90% of the starting volume had been removed. The concentrated sample was next precipitated with a double amount of ethanol and centrifuged  for 10 min at 9000 rpm. The supernatant was discarded, while the solid part was dried at 40 °C and powdered in a mortar. Thus, the water extract was obtained. A filter cake left after the liquid part was separated after autoclaving was mixed with sodium hydroxide (1 M) and again autoclaved under the same conditions. The material was then cooled to room temperature, filtered through cotton wool, neutralized, and centrifuged for 10 min at 9000 rpm. As with the water extract, the alkali sample was precipitated overnight with ethanol at 4°. The next day, it was centrifuged, and the solid part was collected and dried at 40 °C and powdered. The dried powdered mushroom was soaked in ethanol , 24 h at 37 °C, before testing antimicrobial activity. The working concentration of the microbial suspension in the appropriate medium was 105 CFU/mL and was adjusted with a McFarland densitometer . The bacterial strains used in this study were Gram-positive The MIC was determined by the broth microdilution method . The MIC5 CFU/mL, a McFarland densitometer  was used. The mushroom extract was dissolved in sterile Milli-Q (MQ) water in such a way as to obtain an initial concentration of 5 mg/mL, and then this solution was transferred to flatbottomed 96-well microtiter plates . The bacterial culture (50 μL), previously prepared in sterile TSB, was added to the mushroom extracts. After 24 h of incubation, the plates were washed three times with sterile MQ water using a microplate washer . The samples were dried at 40 °C, and then a crystal violet solution  was added to them. The dyeing lasted 15 min, so the dye was carefully washed off with tap water. To determine the inhibition of bacterial adhesion, a solution of acetic acid (33%) was added to the dried samples containing L. monocytogenes, while an ethanol solution (96%) was added to those with S. enteritidis, and absorbance was measured at a wavelength of 590 nm using a microplate reader . The corresponding bacterial suspension in TSB was used as a control. The equationAc is the absorbance of the control and As is the absorbance of the sample. To determine the antiadhesion potential of mushroom extracts, the same bacteria as for the MIC assay were used. The antiadhesion ability was determined using a procedure established previously . To adjuThe antibiofilm potential of mushroom extracts was determined using the procedure already described, with the difference that samples in microtiter plates were incubated for 48 h instead of 24 h. In addition, Equation (1) was applied. In this case, the percentage of inhibition of biofilm formation (%IB) in the presence of the appropriate concentration of the mushroom extract was determined.1 and B1 and W2 and B2, respectively:The multi-layer perceptron (MLP) model was used, which is known for its accuracy in approximating non-linear functions , for modWeight coefficients were determined during the ANN learning cycle, with the intention to minimize the error between network results and experimental values ,64.w—weight coefficient in ANN model, i—input variable, j—output variable, k—hidden neuron, n—number of hidden neurons, m—number of inputs.The relative impact of the input parameters on the output variables was calculated using Yoon’s global sensitivity equation, which is based on the weight coefficients of the developed ANN models .(3)RIij2), root mean square error (RMSE), coefficient of determination (r2), mean bias error (MBE), and mean percentage error (MPE) [xexp,i stands for the experimental values and pre,ix are the predicted values calculated by the model; N and n are the number of observations and constants, respectively.The numerical verification of the developed models was tested using reduced Chi-square (χor (MPE) :(4)χ2=∑iThe data were processed statistically using the software package STATISTICA 10.0 . The obtained results are expressed as the mean value with standard deviation (SD). S. enteritidis and L. monocytogenes. Namely, mushroom-derived extracts proved to be efficient food-borne pathogenic bacteria adhesion and biofilm-forming control agents, which is very important due to the unbefitting use of antibiotics and the unseemly control of human infections, which has led to the emergence of resistant bacterial species. Application of alternative sources of antimicrobials, which is proven in this study with 40 different water and alkali-based extracts of 20 different mushrooms, can lead to a decrease in the negative impact on public health and the global economy. For the first time, the ANN models were applied in the investigation of mushroom extracts as anti-biofilm and anti-adhesion agents, so these types of advanced mathematical tools were able to fit the experimental data well and successfully predict the output variables, with a good predictive capability. The overall coefficient of determination (r2) for the inhibition of adhesion and inhibition of the biofilm-forming process was 0.865, which indicates the possibility of using this data analysis for cost- and time-consuming experiments such as this one with a high number of samples. Overall, the natural material tested in this study has several benefits of interest to the food industry, such as solubility, efficiency, and non-toxicity, and it has no bactericidal activity, while at the same time, the proposed ANN model can successfully predict its antibiofilm behavior. The features examined and validated in the presented paper provide a promising avenue for the industrial setting.Discovering mushrooms as a source of novel antimicrobial agents in nature, this study offers the initial case study of their full potential in in vitro conditions against the bacterias


Despite growing epidemiological evidence, the relationship between Parkinson’s disease (PD) and cancer has not been conclusively demonstrated, and related studies are scarce in the Asian population. We aimed to determine the association between PD and subsequent development of various cancers from longitudinal data of a representative sample of Korean adults aged ≥40 years. We retrospectively identified 8381 patients diagnosed with PD from 2002 to 2019 using claims data among 514,866 people of random samples from the Korean National Health Insurance database. We sampled 33,524 age-, sex-, income-, and residential area-matched participants without PD from the same database. The longitudinal associations between PD and overall cancer, as well as 10 common types of cancer, were estimated using multivariable Cox proportional-hazards regression analysis. The adjusted hazard ratio (aHR) of all cancer types was 0.63  in patients with PD compared with matched controls. The aHRs of gastric, thyroid, colorectal, lung, hepatic, and pancreatic cancer and hematological malignancy were 0.69 (0.56–0.85), 0.60 (0.39–0.93), 0.56 (0.44–0.70), 0.71 (0.58–0.84), 0.64 (0.48–0.86), 0.37 (0.23–0.60), and 0.56 (0.36–0.87), respectively. The associations of bladder, gallbladder and biliary duct, and kidney cancer with PD were not statistically significant. Our findings show inverse associations between overall cancer and most cancer types in patients with PD. These inverse associations and their pathogeneses merit further investigation. Parkinson’s disease (PD) is the second most prevalent degenerative disease of the central nervous system (CNS), affecting approximately 1–2% of the world population. PD is characterized by an imbalance in the output of the striatum owing to progressive loss of nigrostriatal dopaminergic innervation, resulting in cardinal motor symptoms, such as bradykinesia, 4–6 Hz resting tremor, rigidity, and postural instability, as well as autonomic dysfunction, psychological changes, and cognitive impairment. Although the exact pathogenesis of PD is still not understood, it is considered a multifactorial disease caused by the interaction of genetic, environmental, and endogenous factors.2. Numerous epidemiological observations also bear out this phenomenon: patients with PD have a lower risk of developing many common types of cancer than do the general population5. However, these epidemiological reports were mostly from Western countries. To our knowledge, only three studies of overall cancer development in Asian patients with PD have been reported, and their results were inconsistent8.The characteristic pathological outcomes of PD are extensive neurodegenerative changes and cell death throughout the nervous system, whereas cancer pathology is based on an increased cell proliferation and resistance to cell death due to uncontrolled cell division. Therefore, from cell cycle perspective, these two diseases are on opposite ends of a spectrum. Although these two disease categories are seemingly unrelated, neurodegeneration and cancer have common molecular properties, such as overlapping genetic and biochemical pathways, implying that genetic background that is protective against cancer may also predispose an individual to neurodegeneration, such as in PD, and vice versaInsight into the connections between these two distinct disorders may elucidate their pathogeneses. As differences in genetic background or susceptibility across ethnicities may modify the pathogeneses of both PD and cancer, more data in Asian populations sharing similar genetic properties are needed to determine the epidemiological relationship between the two diseases.Hence, in this study, we aimed to determine the association between PD and the development of cancer, as well as 10 common types of cancer in particular, in the Korean adult population.After propensity score matching, a total of 8381 patients with PD and 33,524 matched controls were included in the analyses .Figure Sex-stratified analysis revealed aHRs of 0.66 (95% CI = 0.58–0.75) and 0.56 (95% CI = 0.48–0.66), respectively, for the development of any cancer in men and women with PD. The significant inverse associations of PD with gastric, colorectal, and pancreatic cancer were consistent across both subgroups. In addition, while PD was inversely associated with the development of lung and hepatic cancer among men, PD in the subgroup of women was inversely linked to subsequent hematological malignancy Table .Table 3SIn the age-stratified subgroup analyses, only the subgroup of patients with PD aged ≥60 years exhibited associations similar to those observed in the main analysis, with inverse associations between PD and the development of overall, gastric, thyroid, lung, hepatic, and pancreatic cancer and hematological malignancy Table .Table 4AThis nationwide, longitudinal study revealed that the probability of subsequent overall cancer development in patients with PD was 0.63 times that in the matched control sample. Furthermore, we discovered that the probabilities of development of gastric, thyroid, colorectal, lung, hepatic, and pancreatic cancer and hematological malignancy were significantly lower in the PD group than in the control group.11, but not all12. In a study of the risk of cancer development among 11,7863 patients with PD in Sweden, the risk of smoking-related cancers was lower than in participants without PD 13. One study in a Danish population revealed a decreased risk for lung , laryngeal , and urinary bladder  cancer and an increased risk for melanoma/skin cancer  and breast cancer  in 14,088 patients with PD compared with participants without PD14. In a British study of 219,194 patients with PD, lower risks for the development of any cancer  and colon cancer were observed compared with participants without PD, as well as a higher risk for breast cancer and melanoma4. Our discovery of lower probabilities for the development of cancers in patients with PD corroborates the results of European studies (both for cancers associated with and those not known to be associated with smoking), and that of higher risks of melanoma and breast cancer was corroborated in American studies16.Our results of an inverse association between PD and overall cancer and many different types of cancer are consistent with the majority of prior studies’ findings17. In a meta-analysis of 50 observational studies by Catala-Lopez et al., the estimated reduction in malignant neoplasm-related morbidity among patients with PD was 17%, and reductions were especially observed for lung, bladder, bowel, prostate, and uterus cancers and blood malignancies18. A recent meta-analysis, with qualitative synthesis of 23 studies, revealed that patients with PD had a lower overall cancer risk  and lower risk of digestive system, lung, and urinary system cancers19. Hence, a large number of nationwide population-based cohort studies and meta-analyses have provided robust epidemiological evidence for the inverse relationship between PD and cancer.This general inverse association was also demonstrated in a meta-analysis of 29 studies : the aggregate risk for cancer in patients with PD compared with controls was 0.73 (95% CI = 0.63–0.83), and that after excluding skin tumors was 0.69 (95% CI = 0.62–0.78)21. Smoking plays a protective role against the development of PD22, whereas it is directly associated with certain cancer types. This explanation is supported by a meta-analysis in which the decreased risk of cancer in patients with PD was particularly the case for smoking-related cancers (40% risk reduction)17. However, our analysis revealed that, among smoking-related cancers, significant inverse relations with PD were identified for gastric, lung, hepatic, and pancreatic cancer but not for bladder or kidney cancer. Furthermore, certain types of cancer that are not related to smoking may also have a close, inverse association with PD. Therefore, genetic factors likely also lower or raise the susceptibility of patients with PD to malignant neoplasms. From such a genetic perspective, the association and interplay between cancer and PD may be due to shared biological processes, such as mitochondrial dysfunction, oxidative stress, DNA damage, cell cycle abnormalities, inflammatory factors, and impaired mitophagy 23. Transcriptomic association studies have identified combined deregulation of the aforementioned biological processes in both cancer and neurodegenerative diseases, suggesting that shared alterations in biological processes may play a role in the association of PD and cancer26. Third, the most compelling explanations for associations between PD and certain cancer types are communal genetic mutations occurring in both diseases27. Proteins coded by genes implicated in PD pathogenesis are involved in various cellular pathways, and mutations in these genes affect both neurodegenerative and tumorigenic processes. Specifically, α-synuclein, encoded by PARK1, the major protein component of Lewy bodies in the brains of patients with PD, may be involved in certain neoplastic formations, and its downregulation has been observed in the other cancer types29. Dysfunction of parkin, encoded by PARK2, may lead to the growth of certain cancer types and the suppression of others31. Increased expression of DJ-1, encoded by PARK7, has been observed in melanomas and breast, lung, colorectal, uterine, hepatocellular, and nasopharyngeal cancers33. PARK6 (PTEN-induced kinase-1), PARK8 (leucine rich repeat kinase 2), and other proteins also play a role in both diseases36. Despite accumulating evidence based on genetic, cellular, and molecular biology studies of cancer and neurodegeneration, the molecular underpinnings of the link between these two disorders remain unclear. Further investigation is necessary to close the remaining knowledge gaps.Although this was an observational study that did not address to pathophysiological mechanisms, the observed epidemiological links between PD and cancer have several plausible explanations. First, strong environmental and lifestyle factors influence the altered susceptibility to cancer in patients with PD, especially smoking8, only two of which were large-scale, nationwide surveys have been conducted in the past decade, one in Taiwan and the other in Korea. Western patients with PD are most commonly reported to have decreased risks of stomach, colorectal, lung, blood, and bladder cancer, as well as a decrease in the overall cancer risk. Those discoveries are consistent with those of the Korean study by Park et al.8, but contrary to those of the Taiwanese study by Lin et al.6. In the latter, the 16 of the 19 types of cancer investigated had a higher HR in patients with PD, and the overall risk of cancer was 1.58-fold higher6. Park et al. believed that the inconsistencies in the results of the two Asian studies may be attributed to the differences in the diagnostic accuracy of PD8. Intriguingly, however, our analyses, in which claim codes were used as they were in the Taiwanese study, yielded contrasting results to those in the Taiwanese study, but similar to those in the Korean study, which complicates the apparent association of PD and cancer. We speculated that, over and above genetic backgrounds, various environmental factors, such as diet, lifestyle, physical activity and exercise, alcohol consumption, smoking status, exposure to toxins or pesticides, and medication use, may result in these discordant results among Asian populations.To date, most of the epidemiological studies pertaining to the association between PD and cancer, as well as the latest meta-analysis, were performed in white participants. However, genetic mutations differ across ethnicities, as seen in the disparities in the risk and prevalence of cancer between Eastern and Western populations. However, we are aware of three studies examining the link between PD and cancer in Asians8 is that the study population and the confounding factors adjusted for analyses are different. A previous Korean study published in 2019 used all relevant data accumulated in the National Health Insurance Service (NHIS) database, whereas the present study used data from the Korean NHIS-Health Screening Cohort, a sample of participants aged 40–79 years who received medical checkups between 2002 and 2003. This cohort included information on risk factors obtained from questionnaires and bioclinical laboratory results. Overall, our study had fewer patients with PD than a previous study, but we had a control group with demographic and socioeconomic information  that matched that of the patient group. We also adjusted for the comorbidity index, in addition to well-known risk factors such as alcohol consumption and smoking, which the previous Korean study did not control for.Moreover, the comparison point between our study and another Korean studyThe inverse association with overall cancer and most cancer types in patients with PD in this study were relatively consistent with results in the subgroup analyses based on patient sex. The only exception was observed with kidney cancer, but the result was not statistically significant. In contrast, age slightly affected the inverse association of PD and cancer. No changes were observed for participants aged ≥60 years, whereas the HRs of gastric, colorectal, and lung cancer were not statistically significant in participants aged <60 years. As with differences between countries, environmental factors may also explain these intergenerational differences.Several caveats of our study must be acknowledged. First, the ascertainment of PD was determined using the International Classification of Diseases, 10th edition (ICD-10) codes G20 (Parkinson’s disease), and only patients who visited the clinic more than two times with that code were included in the PD group. However, previous studies defined patients who had newly diagnosed PD as patients who were assigned both the ICD-10 codes (G20) and rare intractable disease (RID) registration code (V124). Unlike these studies, our study did not consider this RID registration code, which is given after qualified physicians evaluate whether the diseases meet the diagnostic criteria for each RID, and only categorized participants as having PD if they had multiple claim codes of the corresponding ICD-10. Consequently, the number of patients with PD in the present study may have been either underestimated or overestimated. Nonetheless, our results are consistent with the results of most previous studies that investigated the association between PD and cancer, including a large-scale study in Korea. Second, we cannot rule out the effects of possible unmeasured confounders, such as coffee intake, physical activity, family history of malignancy, and genetic factors, on the associations between PD and cancer. Third, the potential role of medication use, especially of anti-parkinsonian drugs, may act as a confounding factor, but was not considered in the data analyses. Further investigation of the effect of PD on the cancer risk, controlled for a variety of additional potential confounders, is warranted. Fourth, the increase in visits to health care institutions because of the diagnosis of PD is likely to act as a surveillance bias in interpreting the significant association between PD and cancer occurrence. Furthermore, we found a lower incidence of cancer in patients with PD, which may have led to underdiagnosis of cancer in the PD group because non-motor symptoms of PD, such as fatigue, weight loss, and nausea, can obscure the initial symptoms of cancer. Fifth, pathological changes in PD may begin in the prodromal phase before the onset of classic signs of PD, which may be associated with cancer development. However, estimates of the duration of the prodromal phase range from months to decades, and the features also vary broadly. Thus, it is not easy to clearly define the prodromal phase and determine the association between it and cancer. Moreover, we were unable to identify prodromal PD cases using the data for this study because we identified PD cases and controls from only the claims data without access to clinically detailed information. Although we did not confirm the start date precursor timing in the PD patient group, we defined the index date as the PD clinical diagnosis data and assigned the same index date to the matched control group. Therefore, the conditions for pathological changes in PD, which may be associated with the occurrence of cancer, are equivalent in both groups.Notwithstanding the abovementioned limitations, our study has notable strengths. We analyzed nationwide claims data, allowing all participants to be accurately traced and reducing the loss to follow-up. In addition, the control participants were matched to patients with PD according to the most important confounding factors, including not only age and sex but also income and residential area. Finally, we adjusted extensively for PD- and cancer-related comorbidities and covariates, such as obesity, smoking, alcohol consumption, comorbidity scores, blood pressure, and blood and cholesterol levels, and we performed subgroup analyses to assess the robustness of the main findings. In particular, although smoking status has a pivotal effect on the relationship between the two diseases, no adjustment for smoking history was made in the statistical models of most prior studies. Thus, our study provides sufficient additional support for the relationship between PD and cancer, a matter of some controversy in the literature.In our investigation, patients with PD had lower probabilities of subsequent cancer and different types of cancer than did participants without PD. Further research is warranted to replicate our findings and to clearly explain the biological mechanisms of the apparent inverse association between PD and cancer.37.Participants in this study were selected from the Korean NHIS-Health Screening Cohort database, which includes details regarding health insurance claim codes (for procedures and prescriptions); diagnostic codes, according to the ICD-10; death records; socioeconomic data; and health check-up data. To construct the NHIS-Health Screening Cohort database, a sample cohort was selected from the 2002 and 2003 health screening participants, who were aged between 40 and 79 in 2002 and followed up through 2013. This cohort included 514,866 health screening participants who comprised a random selection of 10% of all health screening participants in 2002 and 2003This study was approved by the ethics committee of Hallym University (2019-10-023), and the requirement for written informed consent was waived by the Institutional Review Board because this was a recording-based study with no patient contact. We conducted all analyses in accordance with the guidelines and regulations of the ethics committee of Hallym University.n = 9437), from a total of 514,866 participants with 895,300,177 medical claim codes. The diagnosis of PD was determined using the ICD-10 code G20 (Parkinson’s disease), and only patients who visited the clinic ≥2 times with that code were included in the PD group. Moreover, we excluded patients who had first been diagnosed with PD in 2002 from the analyses .We initially selected participants newly diagnosed with PD from January 1, 2002 to December 31, 2019 .The remaining individuals in the database , diastolic blood pressure , fasting blood glucose (mg/dL), total cholesterol (mg/dL), and CCI.Participants were allocated to 10 age groups, with 5-year intervals, from 40-44 to 85 years old and older. Participants were stratified into income classes, from class 1 (lowest income) to class 5 (highest income). The region of residence was defined as urban  or rural .2) with the following categories: <18.5 (underweight), ≥18.5 to <23 , ≥23 to <25 (overweight), ≥25 to <30 (obese I), and ≥30 (obese II), as stated in the Asia-Pacific criteria38. The CCI, which is used to assess 17 comorbidities, ranges from a score of 0 (no comorbidities) to 29 (multiple comorbidities)39. The CCI in this study was calculated for 15 comorbidities, excluding cancer and metastatic cancer.Participants’ smoking status were defined as nonsmoker, past smoker, and current smoker. Alcohol consumption was classified according to frequency: <1 time a week and ≥1 time a week. Obesity was determined using the body mass index , thyroid cancer (C73), colorectal cancer (C18 to C21 and D010 to D013), lung cancer (C34 and D022), hepatic cancer (C22 and D015), bladder cancer (C67 and D090), pancreatic cancer (C25 and D017), gallbladder and biliary duct cancer (C23 and C24), kidney cancer (C64), and hematological malignancy (C81 to C96). We included only participants who were diagnosed with the same ICD-10 code at least twice to select patients with severe cancer.Descriptive statics are presented using frequencies and proportions for categorical variables and means with standard deviations for continuous variables. Propensity-score overlap weighting was performed for exact matching of participants according to covariates and to determine the effective sample size. The propensity score was calculated via multivariable logistic regression with all relevant covariates. Overlap weighting was calculated with a range of 0 and 1; participants in the PD group were weighted according to the probability of the propensity score, and control participants were weighted according to the probability of one minus the propensity score. The standardized difference was used to compare the demographic and clinical characteristics between the PD and control groups before and after weighting. An absolute standardized difference of <0.20 represented a good balance between the groups for an included variable.Propensity-score overlap-weighted Cox proportional-hazards regression analysis was used to estimate HRs and 95% CIs for overall cancer and each of 10 different cancers among patients with PD compared with control participants. In addition to the unadjusted model (crude model), multivariable Cox proportional-hazards analysis was conducted to adjust for different potential confounders measured at baseline. We controlled for the covariates of obesity, smoking status, alcohol consumption, and CCI scores in model 1 and additionally adjusted for SBP, DBP, fasting blood glucose, and total cholesterol in model 2. Time to development of overall and each of 10 cancers in participants with and those without PD was calculated using Kaplan–Meier curves and compared using the log-rank test.We conducted subgroup analyses with respect to age (<60 years old vs ≥60 years old) and sex (men vs. women), using stratified Cox proportional-hazards models.P-value < 0.05 was deemed significant. All statistical analyses were conducted with SAS version 9.4 .A two-tailed


For patients of primary brainstem hemorrhage (PBH), it is crucial to find a method that can quickly and accurately predict the correlation between status of consciousness and PBH.To analyze the value of computer tomography (CT) signs in combination with artificial intelligence (AI) technique in predicting the correlation between status of consciousness and PBH.A total of 120 patients with PBH were enrolled from August 2011 to March 2021 according to the criteria. Patients were divided into three groups  based on the status of consciousness. Then, first, Mann–Whitney U test and Spearman rank correlation test were used on the factors: gender, age, stages of intracerebral hemorrhage, CT signs with AI or radiology physicians, hemorrhage involving the midbrain or ventricular system. We collected hemorrhage volumes and mean CT values with AI. Second, those significant factors were screened out by the Mann–Whitney U test and those highly or moderately correlated by Spearman’s rank correlation test, and a further ordinal multinomial logistic regression analysis was performed to find independent predictors of the status of consciousness. At last, receiver operating characteristic (ROC) curves were drawn to calculate the hemorrhage volume for predictively assessing the status of consciousness.Preliminary meaningful variables include hemorrhage involving the midbrain or ventricular system, hemorrhage volume, grade of hematoma shape and density, and CT value from Mann–Whitney U test and Spearman rank correlation test. It is further shown by ordinal multinomial logistic regression analysis that hemorrhage volume and hemorrhage involving the ventricular system are two major predictors of the status of consciousness. It showed from ROC that the hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL correspond to consciousness, MCS or coma, respectively. If the hemorrhage volume is the same, hemorrhage involving the ventricular system should be correlated with more severe disorders of consciousness (DOC).CT signs combined with AI can predict the correlation between status of consciousness and PBH. Hemorrhage volume and hemorrhage involving the ventricular system are two independent factors, with hemorrhage volume in particular reaching quantitative predictions. The signs of computer tomography (CT) combined with artificial intelligence (AI) can indicate the correlation between status of consciousness and primary brainstem hemorrhage (PBH) of patients.Hemorrhage volume and hemorrhage involving the ventricular system are two independent indicators of the status of consciousness in PBH patients.The hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL in PBH patients correspond to consciousness, minimally conscious state (MCS) or coma, respectively.1.The primary brainstem hemorrhage (PBH) accounts for 6–10% of intracerebral hemorrhages (ICH), with an incidence of approximately 2–4/100,000 per year, and approximately 60–80% of PBH occurring in the pontine region  CliAll of the above methods for evaluating the status of consciousness are clinically applied and recommended, but the reliability of these evidence is only weak or moderate , and theThe signs of computer tomography (CT) and structural magnetic resonance imaging (MRI) can reflect the sites, hemorrhage volume, and hemorrhage involving the ventricular system, and so on. Because the structural MRI tests take a long-lasting time , it is nIn this study, we retrospectively collected and analyzed CT signs of PBH patients to quickly estimate the correlation between status of consciousness and PBH. We took four steps to complete this study. First, we collected a total of nine metrics that were analyzed by the radiologist in conjunction with the AI technique: gender, age, stages of intracerebral hemorrhage, hemorrhage volume, mean CT value, hemorrhage involving the midbrain, hemorrhage involving the ventricular system, grade of hematoma shape, and grade of hematoma density. Second, we performed a univariate analysis of the above factors to find the factors most likely to be related to the status of consciousness. Six factors were found to be significant. Then, to find factors that can indicate the status of consciousness, an ordered multivariate logistic analysis is performed on these six factors. Ultimately, we find two indicators (hemorrhage volume and hemorrhage involving the ventricular system) can indicate the status of consciousness in PBH patients. In addition, we drew the receiver operating characteristic (ROC) curve to quantitate hemorrhage volume and their relationship with the status of consciousness. The hemorrhage volumes of <3.040 mL, 3.040 ~ 6.225 mL and >6.225 mL in PBH patients were found to correspond to consciousness, minimally conscious state (MCS) or coma, respectively. It not only helps in the diagnosis and therapy of PBH, but also serves as a reference for multi-modal assessment of DOC.2.2.1.We retrospectively collected and analyzed 390 patients with brainstem hemorrhage admitted to Department of emergency and Department of neurosurgery of our hospital from August 2011 to March 2021, and selected 120 PBH patients who met the inclusion and exclusion criteria as follows.Inclusion criteria include that: (1) All patients were diagnosed with PBH  and undeExclusion criteria  include:All procedures performed in this study involving human participants were in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the Medical Ethics Committee of the Second Affiliated Hospital, Army Medical University (2021-Scientific research NO. 089-01). Individual consent from all patients was waived for this retrospective analysis.2.2.Craniofacial cross-sectional CT scans were performed in all patients with the orbitomeatal baselines as baselines and a scan range from the cranial apex to the cranial base. The sequence parameters are as follows: field of view = 2.5 cm; the layer thickness = 1.5 mm/5 mm/10 mm. CT models include: TOSGIBA-Aquilion one 640 (Dynamic Volume CT), GE-Optima CT 660 (128 T), GE-Lightspeed VCT-64. CT data complied with DICOM  standard.2.3.We rated the status of consciousness by Coma Recovery Scale-Revised (CRS-R) , and bas2.4.p < 0.05), finally came to an agreement.An associate chief radiologist and an attending radiologist independently analyzed the CT signs and were analyzed by Kappa  and hematoma density (homogeneous versus heterogeneous). Conceptually , hemorrhWe analyzed hematomas using a categorical scale based on classification of hematoma shape and hematoma density  Figure . The graIn a hematoma, the hemoglobin mainly passes through three forms  prior to red cell lysis and is break down into ferritin and hemosiderin. Based on these forms of hemoglobin, we can define four distinct stages of intracerebral hemorrhage: hyperacute, acute, subacute and chronic .In addition, we analyzed the raw CT images in DICOM  format for all cases of cerebral hemorrhage using DEEPWISE Medical Artificial intelligence auxiliary diagnostic software  . ② The ordinal data including age, grades of hematoma shape, grades of hematoma density, CT values, hemorrhage volumes, which were used by Sperman rank correlation tests.All data were analyzed using SPSS  24.0, and statistical significance was defined as Secondly, to find factors that can indicate the status of consciousness, an ordered multivariate logistic analysis was performed on the statistically significant variables screened in the previous step. In order to satisfy the conditions of ordered multivariate logistic analysis, the continuous variables were grouped in order.Finally, in order to find the relationships between hemorrhage volumes and the status of consciousness in more details, we drew the ROC curve.3.3.1.There were 120 cases with PBH, and the number of cases in different groups classified by the status of consciousness were 50 for consciousness, 26 for MCS and 44 for coma. There were 92 males and 28 females. Age ranged from 9 to 83 years, with a median of 52.85 years. Hemorrhages involving the ventricular system were 20 , and notThere were 44 in regular shapes , 76 in irregular shapes ; and 66 in homogeneous densities , 54 in heterogeneous densities . There were not always a one-to-one correspondence between the shape of a hematoma and its density. We selected some samples of CT images for demonstration .CT values and hemorrhage volumes were both analyzed by AI , and the3.2.3.2.1.p > 0.05), while hemorrhage involving the midbrain or ventricular system were significant by Mann–Whitney U tests , stages of intracerebral hemorrhage were weakly , grades of hematoma shapes and densities and CT values were moderately , and hemorrhage volume were highly  correlated with the status of consciousness  and Test of Parallel Lines .To further identify the factors that best indicate the status of consciousness, an ordered multi-class categorical logistic analysis was used. The significances include the Model Fitting Information (Link function: Logit. p < 0.05] and hemorrhage involving the ventricular system . ② there were no significant correlations among the status of consciousness and grades of hematoma shapes, grades of hematoma densities, CT values, hemorrhage involving the midbrain (It showed that: ① the main factors are hemorrhage volume [OR = exp. (β) = exp. (2.092) = 8.101101 > 1, midbrain .3.2.3.The basic thoughts are that the hemorrhage volumes were tested to conform if it passed the normal distribution test, then verify the pairwise differences between the hemorrhage volumes and the status of consciousness , and the critical value of hemorrhage volume was further determined to lie between consciousness and MCS, and between MCS and coma.3.2.3.1.The probability-probability plots (P–P plots) were used to analyze the statistical characteristics of hemorrhage volumes, and it showed that the points in the P–P plots diagram are approximately a straight line. Thus, hemorrhage volumes accord with natural lognormal distribution .3.2.3.2.F = 56.332, p < 0.05) were conducted for the hemorrhage volumes and the status of consciousness, and Students-Newman–Keuls were used to compare them. It showed that there are pairwise differences (α = 0.05) among the hemorrhage volumes and the status of consciousness  (One-way ANOVA (nd coma) .3.2.3.3.p < 0.05, 95% confidence interval (CI): 0.706 ~ 0.913), the Youden is 0.569, the sensitivity is 0.769, the specificity is 0.800, and the critical value is 3.040 mL.In order to find the critically indicative value of hemorrhage volume between consciousness and MCS, we drew the ROC curve  and it sp < 0.05, 95% CI: 0.738 ~ 0.926), the Youden is 0.587, the sensitivity is 0.818, the specificity is 0.769, and the critical value is 6.225 mL.In order to find the critically indicative value of hemorrhage volume between MCS and coma, we also drew the ROC curve  and it sIn short, PBH patients were indicated to be in consciousness when hemorrhage volume is less than 3.040 mL, to be in MCS when it is between 3.040 and 6.225 mL, and to be in coma when it is more than 6.225 mL.To demonstrate these results, we randomly selected three patients with PBH –E. Patie4.Brainstem hemorrhage is a common serious disease and a common cause of acute or chronic DOC , with poIn addition to the CT signs, we selected three other important fundamental clinical data, namely gender, age, and stage of intracerebral hemorrhage, for analysis. Because gender and age are risk factors for ICH . The detThe aim of this study is to find the most valuable CT signs for DOC diagnosis by analyzing routine CT signs of PBH patients. Radiologists generally analyze the signs of ICH, including the location of the hemorrhage, differences in shape, heterogeneity in density, CT values, hemorrhage volume, and whether the hemorrhage involves the ventricular system.Based on CT signs, we found two of the most important indicators of the status of consciousness in PBH patients. Hemorrhage volume and hemorrhage involving the ventricular system are independent indicators of the status of consciousness. The hemorrhage volume was calculated using AI to avoid human errors , and hemMost previous studies have focused on the relationship between CT signs and prognosis for brainstem hemorrhage, and found that hemorrhage volume is an independent risk factor. Motivated by this, here we observed a quantitative relationship between hemorrhage volume and the status of consciousness in PBH patients. We can simply speculate the status of consciousness from the hemorrhage volume of PBH patients directly. When the hemorrhage volume is less than 3.040 mL, the patients should be conscious. Patient should be in MCS when the hemorrhage volume is between 3.040 and 6.225 mL, and when the hemorrhage volume is more than 6.225 mL, the patients should be in coma. Early treatment of PBH is mainly conservative treatment and surgical treatment  proposedNowadays, CT techniques are widely used, but AI techniques are not widely used in primary hospitals. In practical clinical work, the ABC/2 formula is widely used in calculating the hemorrhage volume in cerebral parenchyma . Here, tThe brainstem is dorsally adjacent to the fourth ventricle and ventrally adjacent to the prepontine cistern, so hemorrhage from the brainstem can easily involve the ventricular system. When hemorrhage involves the ventricular system, a wide range of pathophysiological changes occur, most commonly acute obstructive hydrocephalus. Due to the sudden blockage of cerebrospinal fluid circulation, the brain ventricular system acutely enlarges in a few hours, and it should result in short-term or lasting vision changes, even can be prone to coma . In addiOther factors, consisting of hemorrhage location, shape and heterogeneous density grades, as well as CT values, were not associated with indicating the status of consciousness. The midbrain and caudal diencephalon of brainstem are the key parts of the ascending reticular activating system (ARAS) . HoweverPatients with hemorrhage in brainstem progress rapidly. Once diagnosed, it is necessary to quickly judge and assess the status of disease and immediately to undergo conservative or surgical treatment. The etiologies of DOC are diverse , such asIn recent years, with rapid advances of AI techniques, image omics and machine learning, various prediction models have emerged with ICH patients , 37. HerPreviously, the CT sign was never included in the indication of the correlation between the state of consciousness and the PBH. Here, brainstem hemorrhage is selected to explore and evaluate the status of consciousness as a new perspective, namely CT signs. Currently, CT devices are widely used, which makes it easy to collect data and generalize. When we quantitatively evaluate the status of consciousness, it may be possible to find a new evaluation method based on etiologies and objective examination metrics.In summary, hemorrhage volume and hemorrhage involving the ventricular system are independent factors in indicating the correlation between the state of consciousness and PBH. If the hemorrhage did not involve in the ventricular system, the status of consciousness can be preliminarily indicated according to hemorrhage volume, that is, hemorrhage volume of 0 ~ 3.040 mL indicates consciousness, 3.040 ~ 6.225 mL suggests MCS, and above 6.225 mL means coma. If hemorrhage volumes in PBH were the same, patients with involved in the ventricular system should become worse. If hemorrhage is involved in the ventricular system, the state of consciousness should become worse based on the magnitude of the hemorrhage as judged by the volume of hemorrhage. This provides a valid reference for the clinical diagnosis and therapies of PBH patients. Although, most of the major studies on ICH have focused on the relationship between the amount of ICH and prognosis, less attention has been paid to the correlation between conscious state and PBH. It has been reported that early coma is the prognostic factor of primary brainstem hemorrhage , indicat5.The correlation between conscious state and PBH is only one-sided when only CT landmarks are used to represent it. There are many causes associated with impaired consciousness in PBH patients, such as basic vital signs, electrolytes, etc. The incidence of PBH is relatively low and it is difficult to collect surgical data from a large sample over a short period of time. Patients with PBH are in critical condition and some die immediately due to rapid brainstem failure. Rapid assessment of awareness is an important event in diagnosis and treatment, and CT scanning is the method of choice for PBH diagnosis. The analysis of the state of consciousness through the analysis of CT landmarks is certainly the most direct and simple approach. In the future, more methods, such as EEG and biochemical indicators, will be selected to comprehensively assess the correlation between the state of consciousness and PBH and thus aid in clinical diagnosis and 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 Second Affiliated Hospital, Army Medical University , Chongqing 400037, China. Individual consent from all patients was waived for this retrospective analysis.GL collected, extracted, analyzed, interpreted the materials, and wrote the manuscript. JS, SZ, LZ, and HC took part in collecting samples and extracting data. XZ and ZH were responsible for the schematic diagram within this article and revised the manuscript. ZY and YL provided professional support and revised the manuscript. All authors read and approved the final manuscript.This work was supported by grants from Innovative Research Group Project of the National Natural Science Foundation of China (31921003) and Key Project of Chongqing Medical Scientific Research Project  (2022ZDXM002).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. 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