Streptococcus mutans, Porphyromonas gingivalis, Bifidobacteria, and Streptococcus pneumoniae percentages and the NFKappaB expression. Two-way ANOVA was applied considering group  and sex factors, in addition to cluster analysis. Group effect was significant for %S. mutans  and %Bifidobacteria , with overweight and obesity groups showing the highest levels compared to normal-weight ones, with no significant sex effect. There was no difference in the frequency of gingivitis, P. gingivalis, and S. pneumoniae percentages or NFKappaB expression between groups. Cluster analysis generated three clusters according to body fat accumulation: “Higher %BF,” “Moderate %BF,” and “Lower %BF.” “Higher %BF” cluster was characterized by higher body fat percentage and higher salivary %Bifidobacteria, while cluster “Lower %BF” was characterized by lower body fat percentage and lower frequency of gingivitis (“Moderate %BF” cluster was the contrast). According to nutritional status, a difference in salivary S. mutans and Bifidobacteria percentages was found, with overweight or obesity adolescents showing the highest percentages than normal-weight ones. Besides, a positive relationship between body fat accumulation and Bifidobacteria count was observed, indicating a possible interaction between oral bacteria communities and weight gain.Given the high prevalence of obesity in children and adolescents, the investigation of early markers is of clinical importance to better manage this condition. Thus, the aim was to evaluate the cross-sectional relationship between salivary microbiota, gingival health status, and excess weight in adolescents. A total of 248 students  were included, free of caries lesions and periodontal pockets. Physical examination included measures of height, weight, and body fat percentage (%BF). Oral examination was performed to gather information on dental (DMFT index) and gingival health status. Unstimulated saliva was submitted to qPCR reactions to quantify  Obesity is a prevalent condition associated with a chronic low-grade inflammation that predisposes insulin resistance and the development of type-2 diabetes mellitus. In 2016, over 340 million children aged 5–19 years were overweight or had obesity , which followed all the principles of the Declaration of Helsinki. A convenience sample of 248 consented adolescents were included, who were selected from 12 public schools of the municipality of Piracicaba  in the year of 2016 and participate in all stages of data collection. The signed Assent Form and the Informed Consent Form were gathered from all of them and their parents, respectively. All physical and clinical examinations, including the interview, were carried out on the same day; the total sample of adolescents (248) participated in all stages of the study.The sample size was calculated based on the results of Zeigler et al. , which eAn interview was performed to gather information on dental and medical history and medication use profile, which was performed by a trained examiner (DSA). Female participants were asked about the date of menarche and the use and type of contraceptive medication , 21, 22.The exclusion factors considered were: dental caries lesions (cavities), tooth loss, and periodontal disease ; chronic diseases such as epilepsy, cancer, rheumatoid arthritis, asthma, hypertension, or diabetes mellitus; chronic use of medications such as benzodiazepines, anti-inflammatories, corticosteroids, antidepressants, and contraceptives; use of tobacco or illicit drugs; antibiotic use in the last 3 months ; use of The oral examination was performed at schools with daylight (but not direct sunlight) using mirror, probe, and personal protective equipment; the presence of caries experience was examined using the DMFT index   by a calThe gingivitis diagnosis was performed by the same examiner (DSA), based on subjective and objective measures: the self-perception of gingivitis and the presence of gingival bleeding on probing, which was examined using the Community Periodontal Index (IPC) and WHO probe . The selAnthropometric and nutritional assessments involved measurements of height, weight, body fat mass, skeletal muscle mass, and intracellular and extracellular water using a digital stadiometer and bioelectrical impedance analysis . All examinations were performed at schools, by a trained examiner (DSA) in a private room.2) was used to classify the sample into normal-weight, overweight, and obesity as described earlier , to control variations in the menstrual cycle. All volunteers were instructed to avoid alcohol consumption and physical exercise on the day before the collection.Streptococcus mutans  to quantify the microorganisms, as previously described . The spes mutans , Porphyrngivalis , Streptoeumoniae , Bifidobeumoniae , and toteumoniae . For theeumoniae . After ieumoniae –34. The The standard curves were based on the genome size of each microorganism and average of total oral bacteria available genomes (2.45 Mb), according to Dolezel et al. . SpecifiOne mL of saliva with a preservative solution  was transferred to a conical tube, and RNA isolation was performed with Trizol® Reagent according to the manufacturer's recommendations. RNA quantity and purity were measured by spectrophotometry. Samples with a ratio of 260/230 and 260/280 between 1.8 and 2.0 were considered valid. cDNA was synthesized with the QuantiNova Reverse Transcription Kit (Qiagen) from 1 μg total RNA and according to the manufacturer's instructions. Gene expression was evaluated by RT-qPCR using SYBR Green.http://www.ncbi.nlm.nih.gov/tools/primer-blast/. The sequence of the primer is described below. The following reaction conditions for RT-qPCR were used: 7.5 μl SYBR Green PCR Master Mix (SABioscience), 0.3 μl forward and reverse primers (0.25 uM), 5.9 μl water and 1 μl cDNA, subject to the following cycling condition: 95°C, 10 min; 40 cycles of , using the Applied Biosystem 7500. The reference gene used for normalization of NF-Kappa B expression values was β-Actin .Primers were made using the Primer-Blast platform available at Data were analyzed using SPSS 24.0 software  by one of the authors , considering an alpha level of 5%. Exploratory statistics consisted of means, standard deviation, medians, and quartiles. Normality was tested by the Kolmogorov-Smirnov test and QQ-plot graphs; variables that did not present normal distribution were transformed by the natural logarithm (Ln). Missing values occurred due to salivary analysis, although we opted not to perform any kind of data imputation.The evaluation of oral health parameters comprised the comparison of gingival status between groups using the Chi-square test. In contrast, the DMFT index and the number of sextants with gingival bleeding on probing were compared between groups by Kruskal-Wallis test, considering the sexes separately.group  and sex  effect and the interaction between these factors on the variance observed in %S. mutans, %P. gingivalis, %Bifidobacteria, and %S. pneumoniae, and NFKappaB expression in saliva. Effect size  and the power of the test were also used for interpretation. Previously, the results of the homogeneity test (Levene's test) were evaluated as a premise of variance analysis. A Bonferroni-type adjustment was performed to prevent alpha inflation; thus, the alpha level was adjusted to 0.01.Two-way ANOVA (and Bonferroni post-test) was used to verify the %S. mutans, %Bifidobacteria, %P. gingivalis, %S. pneumoniae, expression of NFKappaB, and the frequency of gingivitis. The pairwise deletion procedure was chosen because of the missing data related to NFκB measures. The final number of clusters was based on the interpretability and reliability of the cluster solution; the silhouette coefficient was considered for internal clustering validation. For descriptive purposes, differences between clusters were assessed by observing the F-value.Data were also submitted to cluster analysis to identify homogenous groups of adolescents according to body fat accumulation. First, hierarchical cluster analysis using the farthest neighbor method for calculating distances between clusters was performed to obtain the dendrogram and analyze the range of clusters for further running K-means . K-meansp = 0.536; female: p = 0.124), frequency of gingival bleeding , and in the frequency of gingivitis  between groups classified according to BMI. Additionally, all three groups were homogeneous for age.group effect was found for %S. mutans; Bonferroni post-test showed that the normal-weight group showed the lowest percentage, with a large effect size and a power >80% (p < 0.001) (sex factor had no effect on %S. mutans and no significant interaction group*sex was observed.< 0.001) . The sexgroup effect was found for %Bifidobacteria with a large effect size and a test power >80%; Bonferroni's post-test found differences between normal-weight, overweight, and obesity groups, with the lowest mean of %Bifidobacteria for the normal-weight group . Of note, F-tests should be interpreted only for descriptive purposes , as the clusters were chosen to maximize the differences between each case and the other clusters. Thus, when considering the measures of %BF, the results of the cluster analysis emphasized the relation between body fat accumulation and %Bifidobacteria, while lower %BF was related to a reduced frequency of gingivitis.Cluster analysis was carried out considering the %BF measured by bioelectric impedance and identified three reliable and meaningful clusters , with anS. mutans and %Bifidobacteria in the adolescents' saliva with different nutritional status. Adolescents with overweight or obesity showed the highest percentages of S. mutans and Bifidobacteria than normal-weight ones. Additionally, a cluster analysis emphasized the relationship between body fat accumulation and %Bifidobacteria, while lower %BF was related to a reduced frequency of gingivitis.The main findings of this study were the differences found in %P. gingivalis in experimental models leads to changes in gut microbiota, which is a possible mechanism for the establishment of diseases associated with periodontitis, such as cardiovascular diseases , Bacteroidetes (20%), Proteobacteria (16%), Actinobacteria (6%), Candidate division TM7 (4%), and Fusobacteria (3%) were the six major phyla found,  while BiBifidobacterium species would improve metabolic status. In this sense, probiotics composed of Lactobacillus and Bifidobacterium have been used to modulate the gut microbiota, improving the intestinal immune barrier, and reducing the production of proinflammatory cytokines  free of comorbidities, which ensured statistical power to detect the large differences observed, and the control of potential confounding factors such as clinical oral status and medication intake . Further studies are needed to understand the role of oral bacteria communities in weight gain. Thus, the next steps should comprise a broader evaluation of salivary microbiota of subjects subjected to nutritional interventions, including the species of Bifidobacteria and S. mutans and Bifidobacteria percentages according to the body mass index and a positive relation between body fat accumulation and salivary Bifidobacteria count, thus suggesting that saliva specific microbial load may be a marker of excess weight in childhood.The study found a large difference in salivary 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 Research Ethics Committee of the Piracicaba School of Dentistry . Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.DA, MK, FF, and PC participated in the study design and conception of the study. DA and KS collected the data and biological samples. DA, LS, and MP participated in laboratory analysis. MK and FF supervised the laboratory analysis. PC performed the statistical analysis. DA, TP, CF, and PC wrote the manuscript. All authors reviewed and approved the final version of the manuscript.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.


Sarcopenic obesity is associated with a higher risk of cardiometabolic disease and mortality than either sarcopenia or obesity alone. However, no study has investigated body shape indices for the assessment of sarcopenia in obese populations. Thus, this study aimed to evaluate the accuracy of body shape indices to assess sarcopenia in nationally representative populations with abdominal obesity.Data from the U.S. National Health and Nutrition Examination Survey (U.S. NHANES) 1999–2006 and Korea NHANES (KNHANES) 2008–2011 were assessed. The association between Body Shape Index and sarcopenia was analyzed using a receiver operating characteristic curve. The Z-score of the log-transformed A Body Shape Index (LBSIZ) cut-off value was defined as that with the highest score of the Youden’s index. Changes in odds ratios (OR) for sarcopenia were investigated using restricted cubic spline (RCS) plots.This study included 8,013 American and 4,859 Korean adults with abdominal obesity. The overall area under the curve (AUC) of LBSIZ for sarcopenia was 0.816 (95% CI: 0.794–0.838) in U.S. NHANES and 0.822 (95% CI: 0.799–0.844) in KNHANES, which was higher than that of the body roundness index, conicity index, and waist to height ratio (p with DeLong’s test <0.001). The cut-off values for the LBSIZ were 1.05  for American men, 0.45  for American women, 1.15  for Korean men and 0.95  for Korean women in the development groups. Comparable results were verified in validation groups. The RCS plot indicated that ORs for sarcopenia rapidly increased with an increase in the LBSIZ cut-off value.The increased LBSIZ could function as a reliable and cost-effective screening tool for assessing low muscle mass in populations with abdominal obesity. The World Health Organization reported that 13% of the world’s population had obesity in 2016, and that the prevalence of obesity has dramatically increased over the last 30 years . ConsideSarcopenia, which is the age-related loss of muscle strength and mass, is a well-known cause of disability, cardiometabolic disease, and mortality . With agTo simultaneously assess obesity and sarcopenia, body composition should be assessed because both BMI and WC are positively associated with fat mass and appendicular skeletal muscle . SeveralThus, this study aimed to evaluate the accuracy of the investigation of body shape indices for the assessment of sarcopenia in nationally representative populations with abdominal obesity from the U.S. National Health and Nutrition Examination Survey (U.S. NHANES) and Korea NHANES (KNHANES).Data from the U.S. NHANES from 1999 to 2006 and those from the KNHANES from 2008 to 2011 were assessed. The NHANES is a cross-sectional survey for samples that are representative of the United States population and is conducted biennially by the National Center for Health Statistics. The U.S. NHANES includes questionnaire-based personal interviews, physical examinations, and laboratory tests. KNHANES is an annual cross-sectional survey for samples that are representative of the Korean population and is conducted by the Korea Centers for Disease Control and Prevention (KCDC). The KNHANES comprises questionnaire-based personal interviews, physical examinations, and laboratory tests. In this study, among 41,478 participants of the U.S. NHANES, we included the data of 8,013 participants with abdominal obesity. We excluded those aged 20 years or younger, those without anthropometric data or DXA data, and those who were not Hispanic, non-Hispanic whites, or non-Hispanic blacks. After applying the exclusion criteria, except for race, for 37,753 KNHANES participants, finally, the data of 4,859 participants were included .WC in the U.S. NHANES was assessed by measuring the uppermost lateral border of the ilium using a flexible tape measure. Whole-body DXA examinations were conducted with a Hologic QDR 4500 A fan beam X-ray bone densitometer ; furthermore, total and regional body compositions were analyzed with DXA scans. Additional details regarding the sample collection and examination method can be found in the NHANES Laboratory Procedures Manual .WC in the KNHANES was assessed by measuring the midpoint of the lowest border of the rib cage and the upper lateral border of the iliac crest at the end of normal expiration. Whole-body DXA examinations were conducted using a QDR Discovery fan beam densitometer , and total and regional body compositions were analyzed with DXA scans. Additional details regarding the sample collection and examination method can be found in the guidelines of the KNHANES , 26.2 in men or <5.5 kg/m2 in women according to the European Working Group on Sarcopenia in Older People 2 (EWGSOP2) , and LBSIZ was calculated using (LBSI-LBSImean)/LBSIstandard deviation. According to a previous study, a simple formula, derived using representative samples for each race, is provided in the supplementary Excel file format [The Z-score of the log-transformed A Body Shape Index (LBSIZ) was calculated based on the regression [ln(waist) = a0 + a1ln(weight) + a2ln(height) + δ]. The log-transformed Body Shape Index (LBSI) was calculated using log [waist/(exp(a0) × weighte format , 33, whiwww.r-project.org) and IBM SPSS Statistics ver. 24.0 . P values <0.05 were considered statistically significant.Demographic characteristics, underlying diseases, anthropometric index, and blood test results were presented as means and standard deviations (SD) for continuous variables and prevalence (%) for categorical variables according to the presence of sarcopenia. The results were compared using an independent t-test and a Pearson’s chi-squared test. The relationship between the body shape indices and ASMI in each case was examined using a Pearson correlation coefficient. The area under the curve (AUC) for sarcopenia cases for each Body Shape Index was calculated using the ROC curve. DeLong’s test was used to statistically verify and ensure superiority of the AUC of the ROC curves when screening for sarcopenia . We diviThis study was approved by the Institutional Review Board of Kangnam Sacred Heart Hospital (IRB No. HKS 2017-07-007). All U.S. NHANES protocols were approved by the Research Ethics Review Board of the National Center for Health Statistics, U.S. Centers for Disease Control and Prevention , and all KNHANES protocols were approved by the Institutional Review Board of the KCDC . All participants volunteered and provided written informed consent before their enrolment. Their records were anonymized before being accessed by the authors. All analyses were performed according to approved guidelines and regulations.This study was conducted with 8,013 American and 4,859 Korean adults with abdominal obesity. Among these, 375 Americans (4.7%) and 331 Koreans (6.8%) had sarcopenia. The baseline characteristics of the Americans and Koreans according to sex and the presence of sarcopenia are summarized in Tables This nationwide population-based study was the first to show that the LBSIZ index is a powerful and reliable indicator of low muscle mass in populations with abdominal obesity. Furthermore, muscle mass was negatively associated with the LBSIZ and conicity indices but was positively associated with the BRI and WHtR. Notably, the LBSIZ index had the largest AUC in both U.S. and Korean populations with abdominal obesity. Moreover, after the analysis with respect to sex, the LBSIZ index maintained superior relationships with sarcopenia than did the conicity index, BRI, and WHtR in both populations.r = -0.26) and a positive association with trunk fat mass (r = +0.45), calculated using DXA [In our study, LBSIZ, the modified form of the ABSI, was the most appropriate screening tool for body shape associated with sarcopenia. Previously, the usefulness of the ABSI as a cardiometabolic risk and mortality indicator was suggested for various populations –39. We dsing DXA . Especiasing DXA . In thissing DXA .Because sarcopenia is associated with major unhealthy outcomes, it requires easy, reliable, effective, and validated screening tools that are easily applicable for community-dwelling older adults. Therefore, the revised EWGSOP2 recommended screening tools to identify and assess sarcopenia in clinical practice before obtaining confirmation with DXA, BIA, MRI, or CT . GeneralMeanwhile, limited studies have assessed the risk of sarcopenia using anthropometric parameters. The calf circumference, mid-arm muscle circumference, and skin fold thickness were previously introduced as diagnostic substitutes for sarcopenia in the absence of other available diagnostic methods for muscle quantity, and they reflect survival and physical performance in older people , 23, 28.In this study, low muscle mass was defined as cut-offs of the ASMI according to the EWGSOP2 and AWGS. Previously, it was suggested that body size was an important factor for the establishment of cut-off points for low muscle mass because of the powerful correlation between body size and muscle mass. Walowski et al. showed that the cut-off and average values for the skeletal muscle mass index rose with an increase in BMI classification for healthy Caucasian men and women . KrzyminIn our study with two different populations, LBSIZ was inversely correlated with ASMI and positively correlated with WC. The optimal LBSIZ cut-off point was higher in the Korean population  than in the American population . LBSIZ had a good sensitivity (77.1–88.0%) and specificity (70.6–81.5%) for American women and men with abdominal obesity, and had a good sensitivity (74.3–77.5%) and specificity (69.3–77.1%) for Korean women and men with abdominal obesity. Additionally, consistent results were verified when we applied each LBSIZ cut-off points to the NHANES and KNHANES validation dataset. The high sensitivity and NPV of the LBSIZ implied that LBSIZ might be a good screening tool to identify sarcopenia in populations with abdominal obesity. Although we could not provide the exact reason for these race-dependent differences in cut-off values, it may be because Asians have higher adiposity than Caucasians . In addiThis study had some limitations. First, we only investigated these relationships in the American and Korean populations with abdominal obesity; thus, the results should be confirmed in other ethnic and body shape groups. Second, because of the lack of data for hand grip, gait speed, and for the balance, and chair stand tests, we could not evaluate other sarcopenia parameters such as muscle strength or physical performance. Third, WC and body composition were measured by different methods in the NHANES and KNHANES. Therefore, careful interpretation is necessary for the comparison of the NHANES and KNHANES. Nevertheless, our study had unique strengths. This study used credible and standardized databases that were created by the American and Korean governments, which have a huge sample size and extensive information, and include medication, laboratory, and medical diagnosis data. Moreover, we confirmed the muscle quantity or quality using DXA, which is recommended as the standard method for the definition of sarcopenia. Finally, despite the differences in the race and baseline characteristics of the American and Korean populations, the relationship between body shape indices and muscle mass were meaningfully reflected with a similar pattern to the data.We found that increased LBSIZ could function as a reliable and cost-effective screening tool for the assessment of low muscle mass, and thus potentially improve individualized risk assessments compared with previous studies of body shape indices in the American and Korean populations with abdominal obesity. Further studies are required to generalize our results to other ethnic population groups and to ensure the performance of LBSIZ together with muscle strength indicators, which include gait speed, hand grip, and the chair stand test, as a screening tool for sarcopenia.


Knowledge of the physiological renal blood flow in cattle is essential for interpretation of Doppler ultrasound. In this paper, we describe a protocol for obtaining the renal Doppler parameters resistive index (RI) and pulsatility index (PI) in a systematic ultrasound evaluation of the kidney in cattle and provide preliminary reference values for healthy adult Holstein-Friesian cows.There is a notable lack of reference values for the renal resistive indices in the bovine kidney. Ultrasound (US) Doppler evaluation of these indices is a powerful, non-invasive technique for assessing, monitoring and diagnosing renal diseases in humans and other animals . The aims of the present study were to establish a protocol for renal Doppler US in adult healthy Holstein-Friesian cows and to provide reference values for the renal resistive index (RI) and pulsatility index (PI). In cattle, the right kidney is always visible through a right abdominal window. Nevertheless, the left kidney is rarely accessible by transabdominal ultrasound. Doppler evaluation of the kidneys via a transabdominal approach is possible when accessible, but measurements can only be made in the larger vessels at the renal hilum. Normal RI and PI values were respectively 0.49 ± 0.07 and 0.70 ± 0.15 for the right kidney and 0.53 ± 0.05 and 0.79 ± 0.11 for the left kidney. We suggest an upper cut-off value for the RI of 0.63 and for the PI of 1.00 in healthy Holstein-Friesian cows. This is the first report describing normal values for the renal RI and PI in cattle that may be useful in future studies for characterizing different bovine pathologies that affect the renal parenchyma. Ultrasound (US) evaluation of the kidneys is a routine, non-invasive technique used in both human and veterinary practice. B-mode US helps bovine clinicians to distinguish between upper and lower urinary tract infection, focal or diffuse renal involvement, and sometimes between acute and chronic kidney disease ,5,6,7,8.Doppler US of the kidneys provides dynamic information about the renal blood flow associated with renal function  and abouIn pulsed wave Doppler (PWD), characterization of arterial blood flow by the resistive index (RI) and the pulsatility index (PI) enables comparison of the velocity spectrum over time to evaluate the blood flow through the renal vascular bed. Both indices are also influenced by systemic parameters and postrenal factors such as heart rate, hepatic function, urinary drainage, blood pressure, glomerular filtration rate, and renal blood flow or anaemia ,15. HoweAge, sex and body weight (BW) have been studied as potential factors influencing the RI in humans ,19, dogsBoth RI and PI can be altered even with normal or minimal changes in both the blood renal markers and in the B-mode US, indicating that these indexes are early markers in the disease process, e.g., in diabetic nephropathy ,11,19. IResistive indexes values are considered valuable for evaluating diffuse acute or chronic kidney disease in cats ,10 and dAll experiments were performed following Spanish standards for the protection of animals used for scientific purposes. The procedures applied were supervised by the Bioethics Committee of the Rof-Codina Veterinary Teaching Hospital, University of Santiago de Compostela (Spain) and met the criteria for non-invasive procedures (AELU001/19/ALT (08)/ANAT (01)/DBV/01, 14/11/2019).Twenty-five healthy, non-lactating, non-pregnant adult Holstein-Friesian cows, of mean age 7.16 ± 1.01 years and mean weight 541 ± 48 kg, used for teaching clinical examination methods, were included in the study. The cows received a daily maintenance ration of hay (provided ad libitum) and 2 kg of concentrate  throughout the study period. Values of haematological, biochemical and urine parameters were normal in all of the cows . The cowBoth kidneys are retroperitoneal and therefore associated with the dorsal aspect of the abdominal cavity, with the right kidney markedly cranial relative to the left kidney. The kidneys are lobulated, surrounded by perirenal fat, with a well-developed capsule. Superficial lobulation corresponds to parenchymal division in renal lobules or pyramids. The right kidney is positioned at the level of the 12th intercostal space (ICS) and the 2nd or 3rd lumbar vertebra ,28, of aThe left kidney varies in position depending on ruminal distension and can be located from the midline to the right abdomen and rotated to a variable extent, sometimes even coming in contact with the right abdominal wall, normally more ventral than the right kidney . Its dimOne renal artery emerges from each kidney from both sides of the abdominal aorta, the left one slightly caudal and longer than the right renal artery. At the level of the renal hilum , the main renal artery divides along the long axis of the organ into two to four primary segmental arteries, and each of these then divides into one to four secondary segmental arteries distributed throughout the renal parenchyma .®, Esaote, Italy) and depth; frequency and gain were adjusted to optimize the ultrasound image at any time.As part of a general study of the normal abdominal ultrasound examination in adult cows, a transcutaneous abdominal ultrasound exploration of the right abdomen was performed, from caudal to cranial, as previously described ,31. The Transverse and longitudinal B-mode images of each accessible kidney were recorded to measure maximal craniocaudal, lateromedial and dorsoventral diameters , as well as to assess the overall echotexture and echogenicity in the right kidney, in comparison with the liver parenchyma A. Colour-coded Doppler ultrasound superimposed on the B-mode image was then applied to visualize the renal blood supply to identify which vessels were useful for PWD examination. In order to obtain a PWD spectrum, sample size (4–9 mm) and location were adjusted for the vessel of interest, with the aim of obtaining an angle of insonation always less than 60°, and as close to 0° as possible for optimal Doppler signal. Baseline, pulse repetition frequency (PRF) and gain were also adjusted in Doppler mode in order to optimize the Doppler trace, remove artefacts  and improve blood flow measurements. At least three consecutive and similar cardiac cycle waveforms were used to consistently obtain resistive indices for each vessel, and at least three independent measurements were obtained for each accessible kidney B. These j and p < 0.05 was applied in all cases.All statistical tests were conducted using SPSS for Windows v.24  were calculated as:B-mode US of both kidneys (when visible) took between 5 to 10 min long. Doppler measurements were more difficult to obtain depending on individual factors such as cooperation, amount of intestinal gas, availability of the left kidney, and difficulties to locate and obtain quality Doppler measurements. Complete exploration time was not longer than 45 min in any case.None of the cows examined had any B-mode US abnormalities in the kidneys or adjacent structures, and none showed notable discomfort during the procedure. The mid-to-low frequency convex transducer (1–8 MHz) enabled good tissue penetration, with acceptable definition and Doppler signal in the kidneys visualized. The right kidney was visible in all animals, whereas the left kidney was only visible in 3 of the 25 animals. Access in both kidneys was from the right paralumbar fossa, craniodorsal for the right kidney  and in the middle part for the left kidney, and slightly ventral relative to the right kidney see . MedullaThe B-mode dimensions of both kidneys are summarized in All visible kidneys were accessible through the right paralumbar fossa, and Doppler measurements were made at the renal hilum. Transverse and longitudinal planes were useful for aligning sample size in the Doppler mode at the hilum of the right kidney because the renal artery was directed in a lateromedial direction. For the left kidney, a transverse plane was most useful because the renal hilum was positioned in an oblique dorsoventral direction. Doppler measurements of the right kidney were possible in 23 of the 25 animals examined. Doppler traces could not be obtained in two individuals because of a large amount of intestinal gas in the right abdomen that only could be used for comparison of echogenicity and renal dimensions. When evaluating the vessel architecture by means of colour Doppler US, the main renal artery and its main tributaries  were easily visible B. The diThe Doppler waveform of the renal artery and its main tributaries was characterized in all animals as a low-resistance profile  with a sTo the best of our knowledge, this is the first report describing renal resistive indices in healthy, non-pregnant, non-lactating adult Holstein-Friesian cows. The findings serve as a basis for future studies comparing normal and diseased animals and/or different conditioning factors such as pregnancy and milking. Normal ranges of RI and PI are reflected, with proposed cut-off values of 0.63 and 1.00 for RI and PI respectively. The observed Doppler waveform corresponded to a low resistance profile with continuous diastolic flow, but with a small spectral window, indicating a higher velocity profile than more distal arteries . Some tuBoth RI and PI are indirect measurements of blood flow resistance. The renal RI reflects changes in intrarenal perfusion but is also associated with systemic hemodynamics, and it has been suggested to provide useful prognostic information in human patients . Renal RA cut-off value for renal resistive indices is a clinically useful tool for the diagnosis of healthy or pathological status. In the present study, we suggest an upper cut-off value for the RI of 0.63 and for the PI of 1.00 in healthy Holstein-Friesian cows. Different RI cut-off values have been established in human medicine, ranging from 0.58  to 0.70 The limit may be more similar to that in other large animals, but there is no relevant information available in the scientific literature. Recent studies in horses and donkeys ,33 did nDue to the anatomic branching of the renal artery , the ultAs previously pointed out, there was no apparent difference between the right and left kidney, and the values of the RI and PI indices were similar. However, this may have been due to the fact that the left kidney was rarely visualized 3/25) in our study, as previously observed . As far  in our sIt has previously been established that these indices are typically constant in adults, both in humans ,18,19 anRegarding the weight of the animal, most veterinary research has not found any correlation between renal RI and body weight, similarly to our study in cattle. Park et al.  describeUntil now we have only considered healthy individuals, but these indexes can vary in pathological conditions or be affected by different factors such as gestation and/or lactation. For example, it has been reported that increased vascular resistance that could alter these parameters may be more common in dogs with kidney and liver diseases ,15. EndoNone of the animals showed notable discomfort during the procedure, indicating that a standing exploration is a suitable approach for bovine abdominal ultrasound in daily practice. A low to mid-frequency convex array transducer (1–8 MHz) proved ideal because of its wide aperture and optimal combination of penetration and image quality. Although higher frequency and linear transducers provide better image resolution, they are only efficient in a superficial, narrower field of view, making them less useful for exploring the whole kidney parenchyma through a transabdominal window. Both cortex and medulla were clearly defined in our study, in contrast to the study of Seif and Bakr  in whichB-mode echogenicity, texture and kidney architecture were consistent with previous descriptions of normal kidneys, hypo to isoechoic between the renal cortex and the liver parenchyma . The lefIn both right and left kidneys, the craniocaudal diameter was smaller than previously reported, regarding both anatomical  and US ,2,7 measAlthough this is the first study that reports renal Doppler assessment in cattle, we are conscious that our study has some limitations. The inclusion criteria for the animals were normal physical examination with no history of renal disease, urinalysis, and serum creatinine and urea within the normal ranges, and no renal abnormalities in the B-mode US examination. In cattle, renal impairment can be a diagnostic challenge due to ruminal protein metabolism , and US Transabdominal US is a reliable and feasible tool for Doppler evaluation of the right kidney in cows, but only in the main renal artery and primary segmental arteries. Its availability for the left kidney is reduced but reliable when renal parenchyma is visible through the right paralumbar fossa. The technique is time consuming, but it is well tolerated by the animals. We suggest an upper cut-off value for the RI of 0.63 and for the PI of 1.00 in healthy non-pregnant, non-lactating Holstein-Friesian cows. Further studies are required in order to determine the relationship between renal indices and age (first stages of life), breed, sex, blood pressure, BCS, gestational influence, and milk yield, and to obtain reliable cut-off values for kidney pathology and other diseases.


Asthma and dry eye disease are common clinical diseases. Studies have shown that asthma is related to dry eye, but there is no high-quality evidence-based medical evidence.This protocol and final study will be conducted in accordance with the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols 2015 statement. We will search PubMed, EMBASE, ISI Web of Science, China National Knowledge Infrastructure for all relevant literature published from their inception up to August 1, 2020. Literature search, data extraction, and quality assessment will be carried out independently by two researchers, and a third researcher will resolve differences when necessary. The association between dry eye disease and asthma will indicate as odds ratio with 95% confidence interval and statistically analyzed using RevMan 5.3 software. If the studies included have high heterogeneity, we will conduct sensitivity analysis and subgroup analysis.The protocol is intended to guide a meta-analysis aimed at identifying and quantifying the association between asthma and dry eye disease. Patients with asthma often suffer from other allergic diseases, including allergic rhinitis, allergic conjunctivitis, and atopic dermatitis.,8 Recent studies have shown that allergic diseases, asthma, a history of arthritis, gout, use of corticosteroids, antidepressants, and hormone replacement therapy may be risk factors for DED.,10Asthma is a common chronic respiratory disease characterized by inflammation, airway remodeling and hyperresponsiveness.,12 and there is a lack of high-quality evidence-based medical evidence. Therefore, we will collect relevant literature and conduct a meta-analysis to assess the association between asthma and DED.Although a number of studies have investigated the link between asthma and DED, the findings are inconsistent2The purpose of this study is to evaluate the association between asthma and DED through a meta-analysis of published data.33.1 Ethical approval is not required for the study.The protocol has been registered in the Open Science Framework (OSF) (registration number: DOI 10.17605/OSF.IO/UHN38). This systematic review and meta-analysis will be reported inaccordance with the Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement.3.2According to the search strategy proposed by Cochrane, 2 researchers will independently search multiple electronic databases, including PubMed, EMBASE, ISI Web of Science, and China National Knowledge Infrastructure to retrieve all eligible articles published from their inception up to August 1, 2020, without any language restriction. The English database will use a combination of Medical Subject Headings (MeSH) alongside free terms to search for potentially qualified publications  and its 95% confidence interval (CI), which should be either provided directly in the original article or could be calculated based on the original data.3.4Abstracts, editorial letters, reviews, case reports, book chapters, and organizational guidelines were excluded from the present analysis. If studies with overlapping participants were encountered, the reports with the largest sample and the most recent reports were included in the present meta-analysis. If no data are available in the original article, the corresponding author of relevant study would be contacted via email. If the corresponding author did not response after we sent 3 e-mails, this article would not be used for quantitative synthesis.3.5Two reviewers (XX and JW) will independently review all the included literature, extract data, and cross-check. If there are differences of opinion, the third reviewer (YZ) will negotiate and resolve. In the literature screening, the title of the text is read first. After the obviously irrelevant literature is excluded, the abstract and full text are further read to determine whether to include. A flow chart of study selection is shown in Figure 3.6 The methodological quality of the cross-sectional studies was evaluated following the standards of the Agency for Healthcare Research and Quality.Two reviewers (WW and JW) will independently evaluate the quality of the included studies and a third reviewer (YZ) will be consulted for consensus if disagreement occurred. The Newcastle-Ottawa Scale was used to assess the risk of bias in case–control and cohort studies.3.7χ2 test and the Higgins I2 test (P > .1 and I2 < 50% indicated acceptable heterogeneity). A fixed model will be applied to estimate the pooled ORs if low heterogeneity among studies, otherwise the random model will be used.RevMan 5.3  will used for the meta-analysis and subgroup analysis. The association between asthma and DED was estimated using adjusted OR and unadjusted OR, expressed as a 95% CI. The confounding factors considered included age and sex. Before combing date from the included studies, statistical heterogeneity among studies for each outcome was estimated using a standard 3.8The funnel plots will be utilized to analyze the potential publication bias if there are >10 studies. Begg rank correlation test and Egger linear regression test via Stata version 12.0 (Stata Corp LP) will be also used to evaluate the publication bias.3.9We will eliminate 1 study in turn and re-analyze to check the robustness and reliability of pooled outcome results. In the case of high heterogeneity, we will conduct subgroup analysis based on age, sex, and race.3.10The quality of evidence for outcome will be assessed by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) working group approach. High, medium, low, or very low quality represents the 4 levels of evaluation.4,18 Age is known to be an important factor, but the incidence of DED is still around 15% in people under 50 years of age. Therefore, the research of related risk factors is an important method, which helps us to explore the pathological mechanism and preventive treatment of DED. At present, many studies have proved the connection between asthma and dry eye. For example, through a comparative analysis, Dogru et al found that children with asthma have a higher rate of tear film instability, which may lead to future DED. Bielory found that antihistamines and anti-inflammatory drugs used to treat asthma and allergies may exacerbate DED by causing tear film dysfunction or conjunctival overreaction. However, there are also population-based studies showing no significant association between asthma and DED. Therefore, a comprehensive, systematic, and rational meta-analysis is necessary to assess the association between asthma and DED.DED is a common clinical disease with a prevalence of 15% to 35%, which seriously affects the quality of life.To our knowledge, this is the first systematic review and meta-analysis to evaluate the relationship between asthma and DED. However, as an observational meta-analysis, our study has some limitations. First of all, our research cannot reflect the causal relationship between asthma and DED. Secondly, the influence of environmental and drug factors cannot be ruled out. Finally, the lack of a universal “criterion standard” diagnosis of dry eye may have influenced our results. Nevertheless, our research will demonstrate and quantify the connection between asthma and dry eye, and provide references for clinical prevention and treatment.Conceptualization: Qun Huang, Chuantao Zhang.Investigation: Xili Xiao, Jing Wang.Supervision: Wanjie Wang, Juan Wang, Tingting Liao.Writing – original draft: Yang Yang, Chuantao Zhang.Writing – review & editing: Qun Huang, Yanlin Zheng.


Background: Recently, RBFOX1, a gene encoding an RNA binding protein, has consistently been associated with aggressive and antisocial behavior. Several loci in the gene have been nominally associated with aggression in genome-wide association studies, the risk alleles being more frequent in the general population. We have hence examined the association of four RBFOX1 single nucleotide polymorphisms, previously found related to aggressive traits, with aggressiveness, personality, and alcohol use disorder in birth cohort representative samples.Methods: We used both birth cohorts of the Estonian Children Personality Behavior and Health Study . Aggressiveness was assessed using the Buss–Perry Aggression Questionnaire and the Lifetime History of Aggressiveness structured interview at age 25 (younger cohort) or 33 (older cohort). Big Five personality at age 25 was measured with self-reports and the lifetime occurrence of alcohol use disorder assessed with the MINI interview. RBFOX1 polymorphisms rs809682, rs8062784, rs12921846, and rs6500744 were genotyped in all participants. Given the restricted size of the sample, correction for multiple comparisons was not applied.Results: Aggressiveness was not significantly associated with the RBFOX1 genotype. RBFOX1 rs8062784 was associated with neuroticism and rs809682 with extraversion. Two out of four analyzed RBFOX1 variants, rs8062784 and rs12921846, were associated with the occurrence of alcohol use disorder.Conclusions: In the birth cohort representative sample of the ECPBHS, no association of RBFOX1 with aggressiveness was found, but RBFOX1 variants affected basic personality traits and the prevalence of alcohol use disorder. Future studies on RBFOX1 should consider the moderating role of personality and alcohol use patterns in aggressiveness. Globally, more than 1.3 million people worldwide die each year owing to aggressive behavior and violence , accounting for 2.5% of mortality . StrugglRBFOX1, has been linked to aggressive behavior by convergent evidence from GWAS, epigenetic analyses, and neuroimaging genetics, gene expression, and animal models  encodes for the Fox-1 protein and regulates alternative splicing that controls gene expression and, in turn, coordinates neuronal brain activity  are key components in RNA metabolism  by influisorders . Variati anxiety , attenti anxiety , schizop anxiety , 20, aut anxiety , intelle anxiety , and gra anxiety . ConclusRBFOX1 have been associated with aspects of aggressiveness in a number of GWASs  showed suggestive associations. Of these, the rs809682 polymorphism was demonstrated to have the lowest association p-value, with the major T allele conferring the risk. Statistically significant association was found for rs809682 when comparing aggressive prisoners to controls and non-aggressive prisoners  sample, the original Estonian sample of the European Youth Heart Study (1998/99) that was subsequently incorporated into the longitudinal ECPBHS. All the subjects are of European descent. The principles of formation of the original sample and procedure of first data collection have been described in detail elsewhere . In brien = 436 in the younger and n = 499 in the older cohort) rated each statement on a 5-point Likert Scale . During the same data collection waves, the Life History of Aggression interview  was carn = 856) with EE.PIP-NEO  at age 25 by experienced clinical psychologists using the Mini-International Neuropsychiatric Interview  were as follows: rs809682–TAACAAACTACAGCCTAATTTAGTA[A/T]GTGAACTAAGTGAAAGCCTAACTTG, rs8062784–TTCTGTGAACCAACACTTTCTTTTC[A/T]TTGGGTTTGATACAGTGGCATCAAT,rs12921846–ATCTTGGAAAGCATTTGTTATTTCA[A/T]ACTCTTCAAATCTGCAAGTCTTACA, rs6500744–GCTTACCATTTATTTTATTTTCAGG[C/T]GGTTGTATTCATTATAATGCCATTA.Reactions were performed on the Applied Biosystems ViiA™ 7 Real-Time PCR System. The amplification procedure consisted of an initial denaturation step at 95°C for 12 min and 40 cycles of 95°C for 15 s and 60°C for 1 min. Positive and negative controls were added to each reaction plate. No inconsistencies occurred. Genotyping was performed blind to all phenotypic data. Allele frequencies agreed with the National Center for Biotechnology Information database and published reports. Genotype frequencies were in Hardy-Weinberg equilibrium and are shown in F-statistic, raw p-value and eta-squared (η2) as a measure of effect size. Fisher's least significance difference method (LSD) was used in all post hoc comparisons. Contrasts were calculated for significant model effects. Chi-square tests were conducted to assess the distribution of Alcohol Use Disorder by genotype, and by genotype and gender, and presented as χ2-statistic and raw p-value. For fitting of the path model, we used the AMOS package of structural equation modeling (SEM) by the MCMC (Markov chain Monte Carlo) method. Genotype was entered into the SEM model as a dichotomous variable: A/A homozygotes vs. T-allele carriers. All p-values are reported as two-tailed, and results are considered significant at the conventional p < 0.05 level; correction for multiple testing is not applied. Statistical analyses were performed using IBM SPSS Statistics, Version 25.Birth cohorts were pooled for analysis. Categorical variable (genotype) relations to continuous variables were explored with analysis of variance (ANOVA) and presented as RBFOX1 polymorphisms. This was the case for total scores as well as subscales. No genotype by gender effect was found either.Aggressiveness assessed either using the self-report Buss-Perry Aggression Questionnaire  or the LRBFOX1 rs8062784, being lower in homozygotes for the aggressiveness risk allele A  was revealed for RBFOX1 rs8062784 . Female RBFOX1 rs12921846 homozygotes for the less frequent T-allele, also has been related to lower aggressiveness, had higher alcohol abuse risk.Alcohol use is a most salient mediator to aggressiveness, so the association of s8062784 : This was8062784  was asso2 = 102.8; df = 1; p < 0.001). In these birth cohorts, lifetime alcohol use disorder was not associated with income in either male or female subjects (data not shown), probably owing to early age. At age 25, 58% of the participants were living with a spouse, but there was no difference in lifetime occurrence of AUD between subjects who lived with their spouse (21%) compared with subjects who did not (25%). However, the lifetime prevalence of AUD was higher  in females who did not live with a spouse compared with those who did . There was a higher prevalence of AUD among subjects with lower education level at age 25 ; but RBFOX1 genotype was not associated with education (data not shown).Next we examined the association of several factors potentially related to alcohol use disorder at age 25, which is the last observation for both cohorts. AUD was more prevalent in males: 10% of women and 38% of men had experienced AUD by age 25  = 30.01; p < 0.001; η2 = 0.037], lower agreeableness , and lower conscientiousness . Because the RBFOX1 rs8062784 genotype and occurrence of alcohol use disorder were both associated with neuroticism, we examined whether or not the association of the RBFOX1 genotype could be mediated by this personality trait. According to a Bayesian model by the Markov chain Monte Carlo method, the RBFOX1 rs8062784 direct effect on AUD was not significant , the RBFOX1 rs8062784 effect on Neuroticism was 7.69 , and the neuroticism effect on AUD was 0.006 (0.0002…0.009), suggestive of the neuroticism mediated association of RBFOX1 with alcohol use disorder . Thus, somewhat speculatively, lower prevalence of rs809682 T-allele among less aggressive subjects in some studies may indirectly suggest that this allele is promoting assertive behavior, and the absence of it mitigates aggressive behavioral choices.a et al.  of nine a et al. . Furthera et al.  study, ta et al. , 51. Whia et al.  made thea et al. , and exta et al. . Indeed,RBFOX1 variants were associated with alcohol use disorder, rs8062784 in males and rs12921846 in females. In both occasions, higher prevalence of alcohol use disorder was present with the minor variant previously associated with lower level aggression. Problematic alcohol use is often predictive of violent behavior, but in this sample, the risk alleles were not associated with aggressiveness. This result rather converges with the personality findings in that in the risk allele carriers, who constitute large majority of subjects, aggressiveness is not common owing to the generally positive side of these variants. According to this scenario, the RBFOX1 aggressiveness-related variants owe this association to other coinciding genetic or environmental factors. In the present sample, alcohol use disorder was associated with both rs8062784 genotype and neuroticism, and the genotype also with neuroticism. A path analysis supported the possibility of mediation by neuroticism between the genotype and alcohol use disorder. Speculatively, the major rs8062784 allele, promoting lower neuroticism and protective of alcohol use disorder in this sample, may in general be associated with proactive behaviors and thus become associated with anger in different types of environment where the positive side of agonistic behavior cannot be properly channeled.Two of the RBFOX1 has previously been associated with aggression-related phenotypes in a number of GWAS. The present sample is much smaller, but nevertheless, any large direct effect of the genotype would have been detected. We do, however, suggest a few potential mediating mechanisms by which the variants of the RBFOX1 gene may exert an indirect and therefore small effect on aggression that becomes revealed in large samples. The strengths of the study are its standard of data collection performed in the uniform conditions of a laboratory, the strong representation of the regional population, and the solid rationale behind the selection of RBFOX1 as a target. Thus, the findings that RBFOX1 variants appear to be associated with personality traits and alcohol use disorder merit attention in further studies.Analysis simultaneously involving four gene polymorphisms and many comparisons inflates the possibility of false positive findings, and conventional correction for multiple testing would render all associations non-significant. This is a major limitation of the present longitudinal study, in that it is restricted in its sample size. The datasets generated for this study are available on request to the corresponding author.The studies involving human participants were reviewed and approved by Ethics Review Committee on Human Research of the University of Tartu. The patients/participants provided their written informed consent to participate in this study.NF-C, SF, BF, AR, BC, and JH contributed to the conception and design of the study. KL, TK, and JH selected and prepared the questionnaires, and KL conducted interviews. MV, KL, TK, MK, TV, and JH collected the data. MV, KL, and L-MT analyzed the data. MV performed genotyping. MV and JH wrote the manuscript. All authors were involved in the final editing and have approved the manuscript.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.


Yearly visits to the ophthalmology clinic were more frequent in the IRD group , particularly to tertiary medical centers (p < 0.001). The IRD group showed greater odds ratios (OR) for metabolic syndrome-related comorbidities, including hypertension  1.10 to 1.26) and diabetes , and double the average yearly medical cost  and ten times the yearly ophthalmology cost . The average disability level was 54.17% for all subjects. This study revealed the large medical and socioeconomic impacts of IRD on not only patients with IRD, but also their family members and the whole society.This study aimed to evaluate the medical and socioeconomic impacts of IRDs using the nationwide health database and a large hospital-based cohort. This retrospective cross-sectional cohort study used data from the nationwide National Health Insurance Research Database (NHIRD). All patients with IRD from January 2012 to December 2016 were selected from the NHIRD and matched with the general population at a ratio of 1:4. All variables, including comorbidities, medications, service utilization, and medical costs, within 1 year from the date of the IRD diagnosis, were analyzed. Disability data were retrieved from the Taiwan Inherited retinal degeneration Project (TIP), a medical center-based database. A total of 4447 and 17,788 subjects from the nationwide database were included in the IRD and control groups, respectively. The Charlson comorbidity index score was higher in the IRD group (0.74:0.52,  Inherited retinal degenerations (IRDs) are a group of severe retinal degenerative diseases with clinical and genetic heterogeneity. They are estimated to affect approximately 4.5 million people worldwide . Among tTo date, studies have rarely focused on the associated comorbidities or socioeconomic impact of IRDs. Frick et al. reported that patients with RP in the USA had a higher prevalence of ocular disorders, including cataract, glaucoma, and other eye disorders  and thatTaiwan has employed a unique health insurance system called the National Health Insurance (NHI) since 1995. The health insurance premium is calculated according to the monthly income bracket of the insurer,  and the The aims of this study were to explore the medical cost, associated comorbidities, and overall socioeconomic impact of IRDs. The statistical information was retrieved from the databases of the NHI and Taiwan Inherited retinal diseases Project (TIP), a medical-center-based database.This cross-sectional retrospective study was based on the data from Taiwan’s National Health Insurance Research Database (NHIRD). The study protocol was approved by the National Taiwan University Hospital Research Ethics Committee. Due to the anonymity of the data, informed consent was not required.Patients with an IRD-related diagnosis from 1 January 2012 to 31 December 2016 were selected from Taiwan’s NHIRD. Accounting for the shift from the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) codes to the International Classification of Disease, 10th Revision, Clinical Modification (ICD-10-CM) codes in 2016 in Taiwan, patients documented with ICD-9-CM code 362.7x  or ICD-10-CM code H35.5x  were both defined as being diagnosed with IRDs. The documentation of the ICD code was regarded as valid if the code was documented at least twice in the records of outpatient clinics within 1 year or at least once during hospitalization. Study subjects were excluded if the IRD-related diagnosis was documented in 2011 or the years between 2012 and 2015, before the identified year (to prevent duplicate recruitment), if death occurred within 1 year after the first diagnosis, or if the subject had not been enrolled in the NHIRD.For data analysis, people aged <85 years were divided into 18 groups comprising all 5-year age ranges, and those aged ≥85 years were combined into one group. The age groups were further simplified into three main groups  for better demonstration, as shown in The index date was defined to be the first date of the IRD diagnosis, and index year was defined as the year starting from the index date. The entire study population was observed from the index date to the date of death of the subject or end of the study (31 December 2016). All variables  were analyzed within the index year.The urbanization level of the city in which the population and medical services are located or registered was classified into seven categories in a study by Liu et al. . Level 1The level of health-care utilities was classified into four levels according to the yearly appraisal by the Ministry of Health and Welfare, Taiwan, which includes medical centers, regional hospitals, local hospitals, and clinics or others. The appraisal level was extracted from the registration data in the NHIRD.All 17 Charlson comorbidities were included in the analysis using the enhanced ICD-9-CM and ICD-10 codes . To furtThe medications commonly used in metabolic syndrome were classified into drugs for diabetes, hypertension, dyslipidemia, and peripheral arterial disease. Each category was subclassified using the Anatomical Therapeutic Chemical Classification. For diabetes, biguanides (A10BA), sulfonylurea (A10BB), α-glucosidase inhibitors (A10BF), thiazolidinediones (A10BG), dipeptidyl peptidase-4 inhibitors (A10BH), glucagon-like peptide-1 receptor agonists (A10BJ), sodium–glucose co-transporter-2 inhibitors (A10BK), glinides (A10BX), and insulins (A10A) were selected. For hypertension, angiotensin-converting enzyme (ACE) inhibitors (C09AA), angiotensin II receptor blockers (C09CA), renin inhibitors (C09XA), α-blockers (C02CA), β-blockers (C07A), calcium-channel blockers (C08CA and C08D), diuretics , other antihypertensive agents , and other anti-hypertensive combinations  were chosen. As for dyslipidemia, we selected only statins (C10AA) and fibrates (C10AB). Cilostazol (B01AC23) was chosen to be analyzed for peripheral arterial disease. Common managements, including examinations  and procedures  were also identified. The records of medications and managements were analyzed if they were prescribed or ordered within the index year.The total medical cost was classified into ophthalmology- and other specialty-related costs. In other specialty-related costs, detailed classification was made into outpatient and admission costs. Medications and non-medication costs were also calculated in terms of the ophthalmologic costs and outpatient clinics of other specialties. The currency exchange rate between New Taiwan Dollars and US Dollars  was set to be 30:1 in this study.The data of specialties of each medical service or outpatient clinic was extracted from the registration data in the NHIRD. If the medical service was a local hospital or clinic, registration of the main specialty, without that of sub-specialties, was possible.Because best-corrected visual acuity (BCVA) or visual field (VF) data had not been collected in the NHIRD, to explore the disability level of patients with IRD, we retrieved the information from our clinical database. We, the National Taiwan University Hospital (NTUH), launched the TIP in 2015 for the referral of patients with IRD, to provide clinical service and genetic consultation. We used the disability grading system legislated in our country’s law . Patient® software version 9.4 . In the statistical analysis, the paired t-test was used for continuous variables and Mantel–Haenszel test for categorical variables. In ophthalmology-related visits, the chi-square test was used for statistical analysis. All statistical tests were two-tailed, and statistical significance was defined as p < 0.05.All data were analyzed with SASn = 2060), those who expired within 1 year after the first diagnosis (n = 42), and those without enrolment in the NHIRD in 2012 (n = 57). For the 4447 included patients with IRD, the general population was matched in terms of the sex, age, and index year at a ratio of 1:4. The study population comprised 4447 patients with IRD and 17,788 people of the general population. According to the NHIRD, the total number of patients with an IRD-related diagnosis from 2012 to 2016 was 6606. We excluded those with an IRD-related diagnosis made in 2011 (p = 0.13) and the monthly income bracket according to the NHI (p = 0.14). However, the Charlson comorbidity index scores were 0.74 and in the IRD and control groups, showing a significant difference (p < 0.001).p < 0.001). Additionally, patients with IRDs utilized significantly more medical resource from the medical centers. p < 0.001). The increased utilization of medical centers and regional hospitals, rather than private clinics, in the IRD group was consistent at every urbanization level. However, since the medical centers are mostly located in cities, the trend was even more obvious in level−1 and level−2 areas.According to the data retrieved from the NHIRD, the index-year ophthalmology visits from the IRD and control groups were 6.80  and 1.06  times, respectively, showing a significant difference , but patients with IRDs were more likely to develop depression . Patients with IRDs were also more likely to have peptic ulcer disease , chronic pulmonary disease , rheumatologic diseases , renal disease , mild liver disease , and malignancy . However, there was no difference between the two groups in moderate to severe liver disease , metastatic tumors , and severe infections, such as acquired immune deficiency syndrome .Since metabolic-syndrome-related diseases developed more frequently in patients with IRD, we further explored the OR of the commonly selected medications and managements for these diseases B. In genp < 0.001). In the yearly cost for ophthalmological visits, the difference was of nearly 10 times . Nutrient supplements, such as lutein and vitamins, or genetic testing, are not covered in Taiwan’s official health insurance system. Therefore, the cost listed here mostly covered ophthalmological examinations and consultations rather than medications. In other words, the real cost for patients with IRD in Taiwan could be much higher than the number reported here. In addition to ophthalmology, other specialty-related medical costs were also analyzed. The yearly medical cost was higher in the IRD group than in the control group in both outpatient (p = 0.01) and admission (p = 0.01) costs.Yearly medical costs spent within the health insurance system was calculated for both IRD and control groups. p < 0.001.To explore the origins of increased non-ophthalmology medical costs in the IRD group, we further analyzed the usage of different specialties between the IRD and control groups . A diffeIn this present study, we analyzed the first 467 patients recruited in our TIP database who had visited the NTUH in the corresponding time period. Among them, 456 (97.64%) patients had detailed initial BCVA and VF records, available for us to define the official disability level. According to the grading system, 73 (15.63%) patients were not disabled, while the rest of the 383 patients (82.01%) were graded . More paAccording to Bertelsen et al.’s study in Denmark,  the sociSignificantly higher Charlson Comorbidity Index scores were found in our study in patients with IRD. To the best of our knowledge, this is the first study on all kinds of comorbidities accompanying IRDs. Previously, Frick et al. compared the Charlson Comorbidity Index score between the RP and non-RP groups but found no difference . A studyAmong all kinds of comorbidities, chronic diseases, such as metabolic syndrome-related diseases, mainly differed between the IRD and control groups rather than in terms of trauma or accidents, consistent with our clinical observations. Most Taiwanese live in urban areas with family members, and the family style is usually core or extended family, for example, a family with three generations. Therefore, patients with IRD are often well-protected and accompanied. This may prevent them from accidents and trauma but may also further limit their physical activities.Metabolic-syndrome-related diseases seemed to be prevalent as comorbidities accompanying IRDs. Higher ORs were found for nearly all kinds of diseases, including hypertension, diabetes, and other possibly related diseases or syndromes, except for obesity. Previous studies by St-Onge,  Hadaegh,The higher rate of metabolic syndrome in the IRD group may be attributed to the high disability rate and activity limitations. Whitson et al.’s study suggested that people with vision impairment had greater odds of mobility disability . Patel eHelicobacter pylori infection rate and use of non-steroidal anti-inflammatory drugs were not collected in our study, a higher stress level probably contributed to the higher odds ratio of peptic ulcer disease [Our results also indicated greater odds of depression in patients with IRD. Similarly, a study by Kim et al. revealed a higher depressive status rate in patients with RP  and anot disease .Our results revealed no difference in the distribution of the city urbanization level between the two groups. However, patients with IRD needed more medical care in medical centers compared to the general population, particularly for ophthalmology. The trend was even more obvious in cities, possibly because medical centers are usually located in cities. The significantly higher mean times of visiting ophthalmology clinics in 1 year in the IRD group reflected the culture and national conditions of our country, implying that medical accessibility and density are high in Taiwan. These patients could easily access medical services when necessary.Among all specialties, the higher visiting rates for neurology, cardiology, endocrinology, physical medicine and rehabilitation, psychiatry, and gastroenterology were consistent with greater odds of metabolic syndrome-related diseases and depression or stress. The lower visiting rates for family medicine and general medicine were correlated with the lower visiting rates of local clinics and local hospitals. Although the age and sex were matched, the visiting rates for pediatrics and obstetrics and gynecology were significantly lower in the IRD group than in the control group. A previous study showed that the marital rate among patients with IRD was lower . The lowOur results from the nationwide health database, NHIRD, demonstrated that the yearly medical cost of a single patient with IRD was nearly twice (194%) that of a person of the general population and that the ophthalmology-related cost was approximately 10 times higher among patients with IRD. Many studies also proved that conditions of visual impairment, blindness, or some kinds of IRDs, such as RP and Stargardt disease, were correlated with higher medical service utilization or medical costs ,15,26,27To evaluate the socioeconomic impact of a disease, both the disease-related cost and total medical needs should be calculated. Our data revealed that both IRD and control groups spent over 80% of their medical cost in specialties other than ophthalmology (and even over 95% in the control group), and over 60% in outpatient clinics. A concomitant finding was that nearly 45% of the outpatient cost of other specialties was incurred by patients with IRD for medications, which is greater than the 37% spent in the control group. Our data of the higher ORs of comorbidities could support this finding. More comorbidities to be treated raises the medical costs in the outpatient clinics.Our study suggested that the mean annual medical cost of each patient with IRD was nearly twice than that of the control, but the difference was merely 1019.7 USD. Frick et al. reported that the annual medical costs of patients with RP were estimated to be 7317 USD higher than those without RP.  The diffAnother uncountable medical cost was generated implicitly from the support of the patient’s family. Based on our own experience, most patients with IRD had to rely on a family member’s support to reach the clinic. Influenced by the Eastern culture, the family’s support and connection between family members in Taiwan are usually strong, which could lower the chances of accidents and trauma for patients with IRD but lead to additional costs from the loss of a partner’s productive forces, possibly further limiting the physical activities of these patients.After summarizing all the explicit and implicit costs and considering the less expensive medical services in Taiwan, the total medical cost should be far higher than it seemed to be. There were limitations to this study. First, although we retrieved the data of a total of 22,235 people from the nationwide database, this was a retrospective cross-sectional cohort study. A future, prospective study may further strengthen the findings. Second, the disability grading level and potential reduction in physical activities were inferred from our hospital-based database rather than the nationwide NHIRD, because no detailed BCVA or VF data could be extracted from the NHIRD. However, since our TIP indiscriminately recruited patients with IRD across Taiwan, encompassing approximately one-fourth of the patients with IRD in Taiwan, the disability trend of patients with IRD should be the same as, or at least similar to, the nationwide NHIRD results. Third, the quantitative relationship between the working disability and the limitation of physical mobility is unclear and warrants further study in the near future. Fourth, as the clinical manifestation of different IRDs varies greatly, the accuracy of the diagnosis and coding is critical for the accuracy of the study results. We could not validate the genetic diagnosis through NHIRD, but we could be confident of the clinical and genetic diagnosis in patients recruited in our TIP cohort, which encompassed approximately one-fourth of the patients with IRD in Taiwan. Finally, there are still some other important disorders that may cause blindness, such as cataract, glaucoma and diabetic retinopathy, but we could not include all the yearly medical costs related to these disorders into our present study. One previous report also revealed increased healthcare costs associated with progressive diabetic retinopathy . FurtherIn summary, this was a nationwide unbiased database study to disclose the impact of IRD on the patient’s socioeconomic status from the basis of comorbidities. To the best of our knowledge, this is the first study using the nationwide database to investigate the relationship between IRD and the greater odds of metabolic syndrome-related diseases and quantified disability level. The results also reflected the family model in Eastern societies and Western cultures. Our results demonstrated that large medical and socioeconomic burdens existed for not only patients with IRD, but also their family members and the whole society. Novel therapeutic methods, including gene therapies, will be valuable to treat these patients or at least maintain their life quality with few adverse effects ,30,31,32To the best of our knowledge, this is the first study using the nationwide database to investigate the relationship between IRD, greater odds of metabolic-syndrome-related diseases and quantified disability level. The results also reflected the family model in Eastern societies and Western cultures. Our results demonstrated that large medical and socioeconomic burdens existed, not only for patients with IRD but also their family members and the whole society. Novel therapeutic methods, including gene therapies, will be valuable to treat these patients, or at least maintain their life quality with few adverse effects.


The obesity epidemic in the United States has been well documented and serves as the basis for a number of health interventions across the nation. However, those who have served in the U.S. military (Veteran population) suffer from obesity in higher numbers and have an overall disproportionate poorer health status when compared to the health of the older non-Veteran population in the U.S. which may further compound their overall health risk. This study examined both the commonalities and the differences in obesity rates and the associated co-morbidities among the U.S. Veteran population, utilizing data from the 2018 Behavioral Risk Factor Surveillance System (BRFSS). These data are considered by the Centers for Disease Control and Prevention (CDC) to be the nation’s best source for health-related survey data, and the 2018 version includes 437,467 observations. Study findings show not only a significantly higher risk of obesity in the U.S. Veteran population, but also a significantly higher level (higher odds ratio) of the associated co-morbidities when compared to non-Veterans, including coronary heart disease (CHD) or angina (odds ratio (OR) = 2.63); stroke (OR = 1.86); skin cancer (OR = 2.18); other cancers (OR = 1.73); chronic obstructive pulmonary disease (COPD) (OR = 1.52), emphysema, or chronic bronchitis; arthritis (OR = 1.52), rheumatoid arthritis, gout, lupus, or fibromyalgia; depressive disorders (OR = 0.84), and diabetes (OR = 1.61) at the 0.95 confidence interval level. Acrs of age . Unfortus of age . For a gs of age . This des of age . Anothers of age . The ress of age . Of particular concern, the Veteran population may suffer not only from obesity but additional risk factors such as post-traumatic stress disorder (PTSD)  and deprThe individual military service experience for each Veteran varies by such factors as military occupation, time in service, number and types of deployments, and assorted stressors such as whether the Veteran served in a combat environment and/or experienced family separation. One unique stressor that all Veterans experience at the end of their military service (no matter how long or how short of a period they served) is their transition from a regimented environment and subsequently adjusting to a new way of life once their military service comes to an end . These cThe research presented here seeks to improve the understanding of the commonalities as well as the differences in obesity rates and associated co-morbidities between the U.S. Veteran population and the nation as a whole. We investigated whether the average Veteran rate of obesity/overweight is similar to that of the U.S. non-Veteran population in the United States when controlling for demographics  and socioeconomics , and hypothesized that Veterans are likely to be more obese/overweight. Secondarily, we looked at the comorbidities associated with obesity, speculating that Veterans are likely to have higher rates of coronary heart disease (CHD) or angina; stroke; skin cancer; other cancers; chronic obstructive pulmonary disease (COPD), emphysema, or chronic bronchitis; arthritis, rheumatoid arthritis, gout, lupus, or fibromyalgia; depressive disorders, kidney disease (not including stones or bladder infections); and diabetes. Recently published data, from the U.S. Centers for Disease Control and Prevention (CDC) Behavioral Risk Factor Surveillance System (BRFSS), provide a rich trove of information that may aid the public health community as well as the VHA in both identifying at-risk sub-groups within the Veteran population, as well as developing health interventions aimed at addressing these threats to their health. For this study, we leveraged the 2018 BRFSS. These data are considered by the CDC to be the nation’s best source for health-related survey data, and the 2018 version includes 437,467 observations. Applying complex weighting to these observations results in a picture of the entire nation’s self-reported health ,30. Research Question 1 (RQ1): obesity/overweight status of Veteran vs. non-VeteranFour variables served as controls for demographics including age in 6-year groups, race/ethnicity based on CDC coding, gender, and marital status. The variables and their associated questions and factor levels are found in Socio-economic status included measures for income level, education level, and employment status. The independent variable of most interest was Veteran status . This caRQ1 assesses the obesity/overweight status as a function of the independent variables. The dependent variable of interest for RQ1 is the obesity/overweight status, and this is measured as a categorical variable in the BRFSS variables of interest for RQ as shown in p is the probability of overweight/obese status (weighted), N is the number of weighted observations, k is the (likely non-integer) number of successes, and ϕ is the variance that is not accounted for by the binomial distribution. Analyses were performed using the survey package for complex weighting [For all RQ’s, we modeled the dependent variable as a function of demographics, socio-economic status, and Veteran status. Because of the categorical nature of the variables and the fact that survey weights are applied which allows for integer variables to have fractional values, quasi-binomial distribution was used. The quasi-binomial distribution allows for the fractional values of integer variables and is thus an improvement over a binomial ,32,33,34eighting :(1)P(X=kProportions for the weighted dichotomous variables are shown in p < 0.001) along with males . After accounting for demographic and socioeconomic variables and Veteran status odds ratio ; those who refused to answer the income question, were not sure, or left it blank, were more likely to be obese  along with those that reported less than a ninth grade education . North Dakotans were more likely to self-report overweight or obese status (1.222).For RQ1, the quasi-binomial model produced the results shown in For RQs 1 through 10, we present the odds ratios for Veteran status along with their associated 95% confidence levels. For all of these research questions, there was an odds ratio greater than one after evaluating the socio-economic, demographic, and geographic variables; however, kidney disease was not statistically different from the non-Veteran population. For arthritis, Veteran status resulted in an odds ratio of 1.26 (Veteran to non-Veteran). For depression, however, the odds ratio is 1.26. The directionality reversed by accounting for covariates, and the effect size (OR = 1.29), is appreciable. Diabetes, skin cancer, and other cancer had odds ratios of 1.10, 1.18, and 1.38 (respectively), while CHD, COPD, and stroke were 1.32 1.46, and 1.28, respectively. In all cases, Veterans were at higher odds for these morbidities. These findings show not only a significantly higher risk of obesity in the U.S. Veteran population, but also a significantly higher level of the associated co-morbidities when compared to non-Veterans. Other studies have looked at obesity and co-morbidities among Veterans, showing a higher prevalence of co-morbidities among the obese members of this population . HoweverThe research clearly shows that obesity is associated with a dearth of illnesses, many of which we looked at in this study ,35. In fOne limitation in this study is that the data originate from the BRFSS which is comprised of self-reported answers to questions which cannot be independently verified. Additionally, self-reported data contain several potential sources of bias that should be noted as limitations including selective memory (only remembering certain aspects of answer), telescoping , attribution , and exaggeration (the embellishment of events).The findings outlined in this study accentuate the problem that obesity has on the health of the Veteran population in the U.S.: a problem that impacts more Veterans than the average American and is continuing to grow in magnitude. However, our study findings also pointedly highlight a number of additional health conditions that, when taken in concert with obesity, paint a concerning picture of the overall health risks or morbidities suffered by the U.S. Veteran population. These morbidities among Veterans could prompt the VA to re-evaluate the current listing of certain disabilities that the VA presumes were caused by military service (presumptive Service connection). This is because of the unique circumstances of a specific Veteran’s military service and the potential for certain Service-unique exposures. If a presumed condition is diagnosed in a Veteran in a certain group, they can be awarded disability compensation. Future studies should examine the interaction of multiple comorbidities on health outcomes of this population, specifically the interaction of depression, diabetes and obesity. Additionally, it would be valuable to further refine and pinpoint geographic locations where Veteran populations in the U.S. congregate, so as to better resource health intervention programs where they can provide the most benefit to target populations. These results can better inform the VHA and other Veteran-serving institutions on the magnitude of the overall health needs of the Veteran population and help develop more effective health interventions aimed at improving the overall health of the Veteran. By analyzing population-based health data for Veterans when compared to the U.S. population, this might better identify the population of U.S. military Veterans (by specific demographic characteristics) who may benefit from health system interventions aimed at solutions for reducing weight and reducing morbidity from certain health risks . These s


Purpose: To find out the CT radiomics features of differentiating lung adenocarcinoma from another lung cancer histological type.Methods: This was a historical cohort study, three independent lung cancer cohorts included. One cohort was used to evaluate the stability of radiomics features, one cohort was used to feature selection, and the last was used to construct and evaluate classification models. The research is divided into four steps: region of interest segmentation, feature extraction, feature selection, and model building and validation. The feature selection methods included the intraclass correlation coefficient, ReliefF coefficient, and Partition-Membership filter. The performance metrics of the classification model included accuracy (Acc), precision (Pre), area under curve (AUC), and kappa statistics.Results: The 10 features  showed the most stable and classification capability. The 6 classifiers, Logistic regression classifier (LR), Sequence Minimum Optimization algorithm, Random Forest, KStar, Naive Bayes and Random Committee, have great performance both on the train and the test sets, and especially LR has the best performance on the test set .Conclusion: Lung adenocarcinoma can be identified based on CT radiomics features. We can diagnose lung adenocarcinoma with CT non-invasively. Medical imaging can assess the characteristics of human tissues non-invasively and is often used in the diagnosis, treatment guidance and monitoring of tumors in clinical practice. And radiomics can extract and quantify the differences in tumor tissues –4.The radiomics workflow is usually divided into four steps , 5, 6: TThe histological type diagnosis of lung cancer is fundamental in guiding patient management. Lung biopsy is a well-established method for the differential diagnosis of lung lesions , but it This paper tests the hypothesis that Adc can be predicted from another lung cancer histological type (Oth) by radiomics. To invest the evidence of that, we analyzed three independent lung cancer cohorts, built some lung Adc classifiers that can differentiate Adc from Oth without considering the clinical parameters. To our knowledge, this work is the first radiomics-based study to predict Adc from Oth , and the proposed models are non-invasive and cost-effectiveness.p < 0.01) in RIDER (in RIDER  data setPartition-Membership filter (PMF) used the random Committee algorithm as the partition generator to divide the 10 features into 1940 partitions . The minP > 0.05), which can be inferred that the selected 10 features have great ability to diagnose Adc. On the test set, the Kappa statistics are approximately equal to 1 for all models shows that the models have great stability, and the minimum value is 0.923 (Kstar). Meanwhile, the mean absolute errors (MAE) are approximately equal to 0, and the maximum value is 0.09 (Kstar).LR classifier has the best performance on the test set, it also has the highest accuracy, true positive rate (TPR), true negative rate (TNR), precision, and lowest MAE on train set. Followed by RC and NB, which have the highest TNR, precision, and area under curve (AUC) on the test set. It is important to diagnose Adc from Adcs so that patients will get accurate treatment earlier. Radiomics provides a non-invasive and fast method to predict clinical outcomes. It could not only support precision medicine but also be a household diagnostic tool. It is an effective way to use radiomics to support therapy decision-making, which will advance personalized medicine. Radiomics has been applied to a variety of organs and systems such as brain, breast, lung, heart, liver, kidney, adrenal gland, cervix, limbs, and prostate , 10, 11.It has been proved the correlation between radiomics features and tumor phenotype –22. ManyHowever, from the data set point of view, the data sets of these studies only contain Adc and Sqc, and in clinical we can't rule out the existence of other subtypes before lung biopsy. So from the perspective of clinical diagnosis, the study of predicting Adc should include all subtypes of lung cancer as many as possible. Besides, among these studies, the performance of CT radiomics models still needs to be improved.The proposed radiomics models showed great performance in diagnosing Adc both on the train and the test sets. The models are available and can be applied in Weka.In this study, lung cancer patients with various histological subtypes were included in the patient cohorts. We used stratified random sampling to balance the covariates. In feature selection, we first test the stability of the feature using the public RIDER data set. Then pick up the features with classification capability. The selected 10 features show excellent classification ability after PMF and CFS. PMF was used for transforming features and CFS is good at picking the most representative minimum feature subset. It has been proved that PMF can not only solve the problem of binary classification but also improve the accuracy of classification , 30. MeaA few issues regarding the stability and reproducibility of the radiomics features have been raised in recent years –33. MultAlthough we try our best to reduce random errors and ensure the correctness of statistical analysis in this study, there are several limitations. Two cohorts in our study are from public data sets, so we cannot accurately estimate the size and direction of systematic bias. The area of interest of the Lung 1 data set and the Lung 2 data set are delineated in different ways, which will lead to measurement errors. Besides, we need more cases to improve the classification model.In conclusion, CT based radiomics can identify Adc. Therefore, we can distinguish Adc only from CT images. We will include multicenter data to improve the classifier and make it a clinical diagnostic tool.Our work was approved by the institutional Ethics Committee.The tools used for statistical analysis were IBM SPSS Statistics 25.0 (USA), and Weka  .We analyzed three independent data sets including a public RIDER data set , a lung The RIDER data set consists of 31 non-small cell lung cancer patients with two CT scans obtained in an interval of about 15 min. We use this data set to evaluate the stability of features for test-retest.Lung 1 data set consists of 180 lung cancer patients (adenocarcinoma: squamous cell carcinoma: other types of lung cancer: metastasis = 3:1:1:1) from our institutional database in 2010–2018. For these patients, CT images, manual delineations, and clinical data were available. The criteria for patient selection are the same as Lung 2. We use this data set for feature selection.n = 306) and test set (n = 78). Specific patients were selected by pseudorandom numbers.Lung 2 data set consists of 535 lung cancer patients. For these patients, texture features were available. We used this data set for model building and validation. In order to keep the data class balanced on the train and the test sets(adenocarcinoma: squamous cell carcinoma: other types of lung cancer: metastasis = 3:1:1:1) and include as many patients as possible, we randomly divided it into train set . The research of the data set can be divided into two stages: training phase and validation phases. The training phase included CT image acquisition, texture feature extraction, feature selection, and model building. The validation phase included model testing and performance evaluation.The acquisition and processing of Lung 1 and Lung 2 CT images were carried out following Image Biomarker Standardization Initiative (IBSI) . The volLIFEx package  used to The stability of the radiomics features was evaluated by using the RIDER data set. For each patient, we extracted image features from two scans. The stability of each feature was calculated using the intraclass correlation coefficient, where the higher the intraclass correlation coefficient corresponds to the more stable feature .Based on the results of feature stability, The ReliefF algorithm  was used to remove the irrelevant features from the lung 1 data set.The selected features were filtered by propositionalization and partition using the Partition-Membership filter (Partition Membership Filter with option Random Committee in Weka) on Lung 2 train and test sets. It can apply any partition generator to a given feature vector to get these filtered vectors for all instances, and the filtered instances are composed of these values plus class attribute and make as sparse instances .Then we used CFS to filter the results. The CFS can select the minimum feature set that is highly related to the classes. In this feature set, there is a low correlation between features, so feature redundancy can be reduced. That is to say, the final result is the feature set with the highest prediction ability, and there is a low correlation between the features in this feature set.We used 6 machine learning classifiers, including LR(logistic with options -R 1.0E-8 -M−1 in Weka), ensemble learning classifier RF (Random Forest with options -K 0 -M 1.0 -V 0.001 -S 1 in Weka), Sequential minimal optimization(SMO with options -C 1.0 -L 0.001 -P 1.0E-12 -N 1 -V−1 -W 1 -K in Weka), NB (naïve Bayes in Weka), RC (Random Committee with options -S 1 -num-slots 1 -I 10 -W in Weka), and KStar (Kstar in Weka) with 10-folds cross validation. The performance metrics of the classification model included TPR, TNR, accuracy, precision, AUC, kappa statistics, and MAE. All datasets generated for this study are included in the article/All authors listed have made a substantial, direct and intellectual contribution to the work, and approved it for publication.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.