Non-steroidal anti-inflammatory drugs (NSAIDs) are some of the most widely used drugs due to their anti-inflammatory, analgesic and antipyretic pharmacological effects. Gastrointestinal side effects are some of the most severe and frequent side effects of NSAIDs. These depend on the balance of the gut microbiome, the abundance of Gram-negative bacteria, and the amount of lipopolysaccharide released. Therefore, restoring or improving gut bacteria balance with probiotic supplements could prove to be an adjuvant therapy against mild NSAID-induced enteropathy. Twenty-five Wistar albino male rats were divided into five groups. The negative control group was administered carboxymethylcellulose and the positive control group diclofenac (DIC), 8 mg/kg for 7 days, which represented the enteropathy model. Treatment groups consisted of a combination of pro-biotic spores (MSB), amino acids and immunoglobulins supplement (MM), which were also administered for 7 days. We analyzed hepatic injury markers  and creatinine, and inflammatory markers, IL-6, TNF-α, PGE2, iNOS, as well as total antioxidant capacity. The results obtained in the present study suggest that the modulation of the intestinal microbiota by administration of probiotics (Bacillus spores), alone or in combination with immunoglobulins and amino acids, represents an attractive therapy for the prevention of NSAID-induced enteropathy. Nowadays, non-steroidal anti-inflammatory drugs (NSAIDs) are some of the most widely used drugs. Their widespread use is due to their anti-inflammatory, analgesic and antipyretic pharmacological effects. These effects are beneficial in the treatment of many diseases from rheumatic conditions to cardiovascular diseases. The most used NSAID is acetylsalicylic acid, not for the effects mentioned above but for the antiplatelet effect in patients with cardiovascular problems ,2.NSAIDs have various side effects, but for many drugs in this class , the most severe and frequent are the gastrointestinal side effects .The possible mechanisms involved in the occurrence of these effects are: reduction in prostaglandin synthesis and destruction of the mucosal barrier function, binding of LPS and HMGB1 to TLR4 on macrophages with subsequent activation of pro-inflammatory pathways and release of cytokines such as TNF-α and IL-1B. The result is neutrophil infiltration of the mucosa and submucosa of the small intestine, and damage at this level [Thus, the occurrence and severity of NSAID-induced intestinal damage depend on the abundance of Gram-negative bacteria and the amount of LPS released. Based on this information, it is hypothesized that restoring the balance of gut bacteria (correcting dysbiosis) may treat or prevent NSAID-induced damage ,6.The first data on the link between gut microbiota and NSAID enteropathy were reported by Robert et al. in 1977. This team observed that germ-free rats were resistant to indomethacin-induced damage in the small intestine. After that, other studies supported this hypothesis [Bifidobacterium longum BB536 in experimental colitis in rats [Bifidobacterium longum CECT7347 in gliadin-induced enteropathy in rats [The beneficial effect of probiotics in intestinal diseases has been demonstrated in several studies: Bacillus spores,  in rats ,9, Bacil in rats , and Bif in rats .Probiotics are live microorganisms that help maintain and restore the microbial balance in case of dysbiosis. In this class of supplements, spore-based probiotics appear to be more effective than non-spore-based probiotics. This advantage is due to their resistance to harsh conditions such as stomach acids. In addition, they are stable at room temperature.Regarding the efficacy of the spore-based probiotic formulation, it has been shown to reduce intestinal permeability, leading to a decrease in inflammatory cytokines. Thus, spore-based probiotics have a modulatory function in the microbiome . The benAnother nutraceutical agent with demonstrated gut health benefits is serum bovine immunoglobulin (SBI)-containing protein. The administration of SBI preparations has been shown to decrease the severity of enteropathy in animals because it improves intestinal barrier function and permeability . Along wTaking these into account, we considered that probiotic supplements (Bacillus spores) and amino acids with immunoglobulins would be a viable option for mild NSAID-induced enteropathy in experimental animals.In our study, we evaluated the ability of a spore-based probiotic and a product containing amino acids with immunoglobulins  to prevent intestinal damage associated with diclofenac-induced enteropathy in rats.The experimental study “The role of Bacillus spores in diclofenac-induced entheropathy in rats” was conducted according to “Guiding Principles in the Use of Animals in Toxicology” adopted by the Society of Toxicology  and all national laws regarding the protection of animals used for scientific research. The working animal protocol was revised and approved by the Ethics Committee of Iuliu Hatieganu University of Medicine and Pharmacy and by the National Sanitary Veterinary and Food Safety Authority (no. 247/18.02.2021).TM (MSB) probiotic capsules , MegaMucosaTM (MM) powder , and Diclofenac (DIC) (solution 75 mg/3 mL). All products were administered orally as a suspension in 1 mL of 1% carboxymethylcellulose . MSB contains spores from five Bacillus species  and MM is a combination of amino acids , serum-derived Ig concentrate, and bioflavonoids.We used MegaSporeBioticn = 25) Charles River Wistar albino male rats weighing between 230 and 280 g were obtained from the Center for Experimental Medicine and Practical Skills of Iuliu Hatieganu University of Medicine and Pharmacy. The rats were maintained under standard conditions of light (12 h light/dark cycles), temperature (22 ± 2 °C), and humidity. The animals were fed rat chow ad libitum and had free access to tap water. The rats were acclimated under these conditions for three days prior to starting the experiment.Twenty-five , serving as the control group;Group II received 1% CMC and DIC (8 mg/kg body weight), serving as the enteropathy model;9 colony forming units (CFU)/day and DIC (8 mg/kg body weight);Group III received MSB (1 × 10Group IV received MM (700 mg/kg/day) and DIC (8 mg/kg body weight);9 CFU/day), MM (700 mg/kg/day) and DIC (8mg/kg body weight).Group V received MSB , blood, small intestine and liver samples were collected for further analysis. Blood was collected from the retro-orbital  sinus plexus under anesthesia. Serum was separated by centrifugation  and then stored at −20 °C for further biochemical analysis.Aspartate aminotransferase (AST), alanine aminotransferase (ALT) and creatinine were measured by automated biochemical analysis according to the BioSystems A15 instrument protocol. Serum levels of the pro-inflammatory cytokines IL-6, TNF-α, PGE2, iNOS were quantified by the ELISA technique (enzyme-linked immunosorbent assay) using commercially available ELISA kits . AST and ALT were expressed in U/L and creatinine in mg/dl. TNF-α, IL-6, and PGE2 values were expressed in pg/mg liver tissue, whereas NOS2/iNOS values were expressed in ng/mg liver tissue.Total antioxidant capacity (TAC) levels were measured according to a validated method previously described by Erel . The tesFor histopathological examination, harvested intestine segments were preserved in 10% formaldehyde, dehydrated in ethanol, and embedded in paraffin. Sections of 7 µm thickness were prepared, and then they were deparaffinized, rehydrated with ethanol solutions in decreasing concentrations , and stained with hematoxylin-eosin. Histological evaluation was performed with a Leica DM750 Clinical microscope , and images were obtained with a Leica ICC 50 W microscope camera .p > 0.05 is representative of normally distributed data. The next step consisted of applying the test to assess differences in the ANOVA data. Results with statistically significant ANOVA test were further analyzed by Student’s t-tests with Tukey’s correction for multiple testing. The results were considered statistically significant for a p < 0.05. Data analysis was performed using GraphPad Prism, version 8.0.0 for Windows, GraphPad Software, San Diego, CA, USA, www.graphpad.com.To describe the data, we used bar graphs representing the averages of the variables per group and the standard deviations. Since our data are of continuous quantitative type, in the data analysis process we used the Shapiro–Wilk data normality test, where a p > 0.05) for each analyzed group.All analyzed variables  were normally distributed (Shapiro–Wilk Descriptive results from each variable of the groups included in the study are shown below.p < 0.001), and between-group analysis revealed a statistically significant difference between group I and group IV , group I and group V , group II and group IV  and between group II and group V   .p = 0.34); thus, there is no statistically significant difference between the groups . In the test for evaluating the differences between groups, we detected a statistically significant difference between group I and group II  and between group II and group IV   .p = 0.005). Analysis between groups revealed statistically significant differences between the means of group I and group II , group II and group IV  and group II and group V   .p > 0.05), were more evident in the case of ALT (31.77%) vs. AST (10.96%). The probiotic supplement administered in combination with MegaMucosa had a beneficial effect, especially on ALT where it reduced the increase by 23.66% ; therefore, there were no statistically significant differences between the studied groups.For the creatinine data, the ANOVA test was statistically insignificant (p = 0.07), with no statistically significant differences between groups. However, the administered substances, either alone or in combination, reduce the decrease in TAC from 58.33% in the case of group II to 50% for group IV, 41.67% for group V, and 33.33% for group III . Therefore, there is no statistically significant difference in the distribution of the CAT variable between the groups. However, CAT increases upon administration of MSB, MM, or the combination to significantly higher values than in the negative control group  shows a normal structure of the small intestine with intestinal villi, numerous simple tubular intestinal glands lined by polymorphic glandular epithelium, and lamina propria (chorion) with loose connective tissue and a discrete inflammatory infiltrate. The muscularis mucosae, submucosa, tunica muscularis and serosa have a normal histological appearance .Histological examination of the small intestine in animals treated with diclofenac (group II) revealed an abundant inflammatory infiltrate, even with small lymphoid follicles and few neutrophils in the lamina propria. No mucosal erosions are observed, and the submucosa, tunica muscularis and serosa have a normal histological appearance .Histological analysis in groups treated with MSB, MM or their combination , revealed no visible injuries to the structure of intestinal mucosa or other layers of the intestinal wall. .Through the present study, we aimed to provide new evidence regarding the protective effect of probiotics containing a combination of Bacillus spores either alone or in combination with an immunoglobulin and amino acid supplement in mild NSAID-induced toxicity, especially in the intestinal environment. Diclofenac has been shown to cause intestinal damage and increase intestinal permeability and bacterial translocation. This NSAID also alters the composition of the intestinal microbiota, increasing the abundance of Proteobacteria and Bacteroides and decreasing Firmicutes in the rat ileum ,19.It is known that PGs have an important role in maintaining blood flow at the gastrointestinal level and also an essential role in mucus production. Administration of NSAIDs causes a reduction in PG levels and damage to the small intestine .In our study, a statistically significant decrease in PG level is observed in the group treated only with diclofenac, in contrast with a significant increase in the groups treated with a combination of diclofenac and MSB, MM or MSB and MM. The role of intestinal bacteria in the induction of enteropathy is recognized in many studies. Some experimental studies have showed that germ-free animals (rodents) have a minimal or even absent risk of developing intestinal injury when taking NSAIDs, but after bacterial colonization with Gram-negative bacteria, the susceptibility of the small intestine to post-NSAID lesions increases significantly .iNOS expression is known to be modulated by cytokines. They play an important role in regulating the immune system, a system that contains both pro-inflammatory and anti-inflammatory cytokine factors. Probiotics have been shown to inhibit the activation of Nf-kB, an activation that triggers inflammatory mechanisms with the increase in adhesion molecules and pro-inflammatory cytokines. The activation of iNOS and COX-2 is also influenced by this pathway .In the present study, diclofenac did not cause significant raised expression of iNOS in liver tissue, and MSB and MM prevented the expression amplification, but the values did not have statistical significance. Changes in the iNOS levels also depend on the tissue in which they are determined. It is possible that the changes are further expressed at the level of the renal tissue, and particularly at the level of the renal cortex. However, not all NSAIDs cause significant changes in iNOS expression. For example, aspirin and celecoxib do not cause significant changes in iNOS at the myocardial level .TNF-α and IL-6 are pro-inflammatory cytokines that can disrupt the immune system and amplify inflammation. The results of our study show that the TNF-α level increased significantly in the diclofenac group, and the studied substances  or their combination prevented the increase, which translates into a protective effect of these substances.Differences between groups regarding IL-6 levels showed statistical significance only between the group with diclofenac and the one treated with MM. However, we observed a 20.62% decrease in the mean of IL-6 in the group treated with MSB compared with the group that received only diclofenac. Looking at the values obtained, both for TNF-α and for IL-6, the anti-inflammatory effect of MM can be deduced, as well as the moderate improvement of inflammation in the groups treated with MSB or MSB+MM. Although some of these results are consistent with the changes observed in the histopathological analysis, similar studies conducted in larger groups of rats could confirm these hypotheses which in the present case are devoid of statistical significance.During cellular respiration, reactive oxygen species are generated in the body. Under physiological conditions, the body’s antioxidant systems have the ability to rapidly neutralize these compounds. In pathological conditions, however, antioxidant systems are overwhelmed, and there is a tendency to accumulate reactive species, with destructive consequences on proteins .Oxidative stress is a condition frequently associated with intestinal damage, especially in the presence of NSAID-induced enteropathy .No statistically significant results were obtained when we measured the parameters for oxidative stress . However, the administered substances, either alone or in combination, reduce the decrease in TAC from 58.33% in the case of diclofenac administration, to 50% for the group treated with DIC and MM, 41.67% for the group treated with DIC, MM and MSB, and even 33.33% for DIC and MSB. These results are encouraging for future research on larger groups of animals.In addition to intestinal toxicity, diclofenac also causes liver and kidney toxicity. This has been evidenced by increased liver enzymes  and increased creatinine. Hepatotoxicity has been observed and objectified by increased liver enzymes in other studies as well, showing the presence of injury at the hepatocyte level .Administration of MSB, MM, or the combination resulted in reduced increases in AST and ALT. This beneficial effect is not statistically significant, but we must take into account the limitations of the study. For ALT, the values decreased below those of the control group after administration of the test substances. The hepatoprotective effect of Bacillus spores was also demonstrated in another experimental study that investigated the effect of this supplement in paracetamol-induced hepatotoxicity .The histopathological results support the obtained biochemical results. The analysis of the intestine tissue sections showed that in the animals treated only with diclofenac, there is an abundant inflammatory infiltrate with the presence of neutrophils in the chorion structure of the intestinal mucosa. However, no mucosal erosions were observed, and the underlying structures retained their normal appearance. This may be due to either the inadequate duration of NSAID exposure or the low dose used, although these were consistent with those used in the literature.NSAID therapy, especially in some chronic inflammatory diseases, is recommended for long-term use. The duration of therapy is directly proportional to the risk of adverse reactions. For this reason, it is necessary to prevent the injuries induced by this pharmacotherapeutic class in the long term with safe and effective substances .Additionally, the cardiovascular risk of COX-2 selective NSAIDs limits their use and therefore the recommendations for classic NSAIDs remain high .The results obtained in the present study suggest that the modulation of the intestinal microbiota by administration of probiotics (Bacillus spores), alone or in combination with immunoglobulins and amino acids, could represent an attractive therapy for the prevention of NSAID-induced enteropathy. Further studies, both experimental and in human subjects, are needed to support the results obtained in the current study.


The disease pathology for diabetes mellitus patients with chronic kidney disease (CKD) may be diabetic nephropathy (DN), non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is of significance. Renal pathological biopsy is the gold standard for diagnosing DN and NDRD. However, it is invasive and cannot be implemented in many patients due to contraindications. This article constructed a new noninvasive evaluation model for differentiating DN and NDRD.We retrospectively screened 1,030 patients with type 2 diabetes who has undergone kidney biopsy from January 2005 to March 2017 in a single center. Variables were ranked according to importance, and the machine learning methods  were then used to construct the model. The final model was validated with an external group .In total, 929 patients were assigned. Ten variables were selected for model development. The areas under the receiver operating characteristic curves (AUCROCs) for the RF and SVM methods were 0.953 and 0.947, respectively. Additionally, 329 patients were analyzed for external validation. The AUCROCs for the external validation of the RF and SVM methods were 0.920 and 0.911, respectively.We successfully constructed a predictive model for DN and NDRD using machine learning methods, which were better than our regression methods.ClinicalTrial.gov, NCT03865914. As lifestyle changes, the number of diabetes mellitus (DM) patients increases globally, particularly in those with type 2 DM (T2DM) . The latThe disease pathology for DM patients with CKD may be DN, non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is significant . CompareSome indicators, such as diabetic retinopathy (DR), DM course, and Hb could help in identifying DN and NDRD –12. HoweIn our previous study, we used the regression method to establish the distinguishing model , 14. CurUsing renal pathological biopsy as the gold standard, we established a noninvasive differential diagnostic model based on SMM and RF to distinguish DN and NDRD patients.This retrospective study included 1,030 consecutive patients with type 2 diabetes who required kidney biopsy at our institution from January 2005 to March 2017 for model development. Additionally, we screened 338 patients from April 2017 to April 2019 at our center for external validation. The variables used for external validation were the same as the variables in the development set. This study was attached to a registered clinical trial [ClinicalTrial.gov. Registry (NCT03865914)].The study protocol was approved by the Medicine Ethics Committee of the Chinese People’s Liberation Army General Hospital . Each patient provided written informed consent before their participation in the study. All patients were screened according to the protocol shown in All patients underwent kidney biopsy after signing the informed consent form. The indications for kidney biopsy were consistent with our previous standards . The kidType 2 diabetes was defined according to the World Health Organization criteria . DN was Baseline characteristics and clinical parameters were collected from all patients before kidney biopsy. Baseline characteristics included age, sex, body mass index (BMI), blood pressure (BP), and medical history of DM and/or hypertension. Laboratory data obtained included measurements of HbA1c, hemoglobin (Hb), serum creatinine (sCr), serum albumin (ALB), estimated glomerular filtration rate (eGFR), and serum lipid levels. Variable definitions have been provided in previous studies .The variable importance of all 49 candidate variables (listed in All processes are shown in Model construction steps: the entire modeling used RF and SVM models. RF modeling used the ranger module in the R language (parameter: importance = “impurity”), and SVM modeling used the kernellab module in the R language . The detailed modeling steps are described as follows:(1) Random forest and support vector machine modeling were performed for 929 samples in the training set  (note: the steps were performed on the RF and SVM models respectively).(2) The RF model was used to screen 49 variables, and finally, 10 features were determined as variables in the final modeling.(3) The 929 samples of the training set and the 10 final selected variables were used to perform five-fold cross modeling , and the modeling results were evaluated.(4) Modeling was performed with all 929 samples.(5) The final model was constructed using all the samples, and the 329 externally reserved samples were used as the test data set; model evaluation was performed, and the receiver operating characteristic (ROC) curve was drawn.The RF machine learning algorithm is an ensemble tree method that can generate many regression trees to detect interactions. At each split, a candidate variable that maximizes the difference in cumulative hazard between the daughter nodes was chosen, and the splitting stopped at the terminal nodes when the data at hand can be split such that each terminal node has at least one unique outcome .The SVM algorithm was originally proposed by Vapnik and colleagues in 1963 . It creaLogistic regression was performed using SPSS version 20.0 . Accuracy and effectiveness were calculated using the formulas previously established by Zhou Jianhui (2008) and Liu Moyan (2014) at our center , 10, whiThe remaining statistical analyses were performed using SPSS version 20.0  and R version 3.5.1  . ClinicaIn total, 929 patients were included in the development set and assigned to one of the two groups (DN and NDRD), based on the outcomes of the kidney biopsy. Patient characteristics are shown in The results of the kidney biopsy indicated that 329 (35.41%) and 600 (64.59%) patients had DN and NDRD, respectively. Numerous pathological subtypes were observed in the NDRD group; membranous nephropathy was frequently observed (32.33%), followed by IgA nephropathy (30.83%), and then mesangial proliferative glomerulonephritis (6.00%) , sCr, and ALB levels  for RF and SVM, and the best combinations are listed in The performances of RF and SVM are shown in In total, 329 patients were enrolled for external validation, and their characteristics are presented in The comparison among the four models showed that RF and SVM do have better diagnostic performance than logistic regression models (Although some CKD patients have a clear history of diabetes and other complications (such as DR), which are clinically suspected to be diabetic nephropathy, there are still some kidney biopsy results of NDRD or DN combined with NDRD. The incidence of DN and NDRD varies greatly in different studies. The prevalence of DN ranges from 6.5 to 94% with an average of 41.3% –29; NDRDIn our study, membranous nephropathy (MN) was the most common type, accounting for 32.33% of all NDRD cases, followed by IgA nephropathy, which accounted for 30.83%. In previous studies, MN (7 to 35%) was the most common cause of NDRD –37. SomeDR, DM course, Hb levels, PP, and hematuria were among the most important indicators of diagnosis through importance ranking in our study. Same with the previous studies, which reported that the absence of DR , hematurDR ranked first in all indicators; DR was a co-occurrence in 79.3% of DN patients in this study. Previous studies ranged from 37 to 84% –51. In mThe presence of microhematuria in diabetic patients with proteinuria may range from 11 to 76–78% , 57, whiIn our study, the DN group tended to have more severe hypertension than the NDRD group. The systolic and diastolic blood pressures (SBP and DBP) of the DN group were higher than those of the NDRD group, and this result is consistent with that in our previous study, which reported that lower BP was a good predictor of NDRD , 13, 59.Kidney biopsy is the gold standard method for diagnosis, but it cannot be performed on all patients because of contraindications  and reluctance to undergo biopsy. As it is an invasive technique with certain risks, such as hematuria and perirenal hematoma, arterial embolization might be required , 62. MorThe previous non-invasive identification guidelines widely used internationally are the 2007 KDOQI guidelines , which wMachine learning has been used in many diabetes-related CKD studies, such as genotype–phenotype risk patterns  and enseThis study had several limitations. First, the time span of patients included is quite large (2005–2017); thus, the disease patterns for DM patients combined with CKD may change over this long period. Therefore, we built a new model using a new population (2015–2017), and it was verified externally. The 2015–2017 model did not show better performance  for the publication of any potentially identifiable images or data included in this article.WZ: Design of the experiment, data statistics, and model building. XL: Data collection, statistical analysis, and model building. ZD and QW: Data collection. ZP: Statistical analysis and model building. YC, YW, and YZ: Collecting clinical data. PC and ZF: Kidney biopsy. XS, GC, and XC: Design of the experiment. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This study was supported by the National Natural Science Foundation Of China (32141005), the Science & Technology Project of Beijing China (no. D171100002817002), the Beijing Municipal Science and Technology project (no. Z181100001918015), the National Basic Research Program of China (no. 2015CB553605), the National Key R&D Program of China , the Natural Science Foundation of China , and the Specialized Scientific Program of the Hainan Province Academician Innovation Platform (YSPTZX202026).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


As hip circumference increases, with 1 SD increase in hip circumference, the risk of POAG increases by approximately 119%  estimated by IVW, there were not heterogeneity and pleiotropy as for the result. Our study for the first time confirms that obesity might increase the risk of POAG using two-sample MR analysis. These results might provide guidance on the prevention and treatment of POAG.The correlation between obesity and primary open-angle glaucoma (POAG) has not yet been fully established. The aim of this study was to investigate the causal relationship between obesity and POAG by a two-sample Mendelian randomization (MR) study. In this study, body mass index (BMI), an index to evaluate general obesity, and waist and hip circumference, indices to evaluate abdominal obesity, were selected as exposures in MR analysis. Single-nucleotide polymorphisms (SNPs) were chosen as instrumental variables (IVs). Summary data from genome-wide association studies (GWASs) based on a European ancestry by Locke et al., with regard to BMI, and Shungin et al., with regard to waist and hip circumference, were used. Genetic predictors of POAG were obtained from public GWAS summary data. To assess the causal effect of obesity on POAG, the inverse variance-weighted (IVW) method was used as the primary method, and other methods, such as MR–Egger, weighted median, simple mode, and weighted mode, were also used as complementary analyses. Finally, we performed Cochran’s Q statistic to assess heterogeneity, and sensitivity analysis was performed to evaluate the reliability and stability of the MR results. MR analysis showed that BMI has a positive effect on the risk of POAG, with 1 standard deviation (SD) increase in BMI; the risk of POAG increases by approximately 90.9% [OR = 1.909; 95% CI= ;  Glaucoma is a leading cause of irreversible blindness worldwide and is mostly characterized by the progressive loss of retinal ganglion cells and their axons . Among t2) in the United States is expected to soar to 50.7% by 2030 (2 were more likely to develop POAG than those with BMI of 18.5–22.9 kg/m2 (2) was significantly correlated with the prevalence of glaucoma , which were based on 1,824 POAG cases and 93,036 controls of individuals of a European descent. Consequently, SNPs were screened, and various statistical methods were used to assess the causal effects of obesity on the risk of POAG.In the present work, obesity-associated indices, including BMI, waist circumference, and hip circumference, were chosen as exposures . We chosp < 5.0 × 10−8); 2) SNPs independent of each other to avoid biases caused by linkage disequilibrium ; or 3) IVs could have an impact on the outcome only through exposure. In a two-sample MR, it is necessary to ensure that the affected allele of IVs in exposure and outcome between different databases corresponds to the same allele. Thus, allele frequency information was used to harmonize the data. The F statistics of each SNP is usually used to judge whether there were weak IVs. F statistics = R2 (n-k-1)/k (1-R2), where R2 is variance of exposure explained by selected instrumental variables, n is the sample size, and k is the number of instrumental variables  and POAG, SNPs were selected according to the following criteria: 1) SNPs highly associated with obesity and significant according to GWAS , pleiotropy tested by using the MR–Egger intercept, and sensitivity by using the leave-one-out test.The standard inverse variance-weighted (IVW) method was applied to primarily analyze the causal relationships between obesity  and POAG . This meP values. Since publicly available summary data were used in this study, the ethical approval was not required.All statistical analyses were performed in R software (version 3.6.1) with the R package “Two sample MR” (version 0.5.6) . P<0.05 was considered statistically significant. Moreover, the Benjamini–Hochberg method was used to obtain the adjusted F-statistics < 10 were excluded. Finally, a total of 31 BMI-related SNPs (the mean of F-statistics was 89.22), 33 waist circumference-related SNPs (the mean of F-statistics was 49.37), and 24 hip circumference-related SNPs (the mean of F-statistics was 68.78) were selected for two-sample MR analysis. All these SNPs are listed in To perform the MR analysis, significant and independent SNPs were extracted, and those with an p = 0.0042; adjusted P = 0.0065)] according to the IVW method. The weighted median  also showed a similar causal relationship between BMI and POAG. The sensitivity analysis showed that there were no heterogeneities  and no directional pleiotropies . Moreover, the leave-one-out test showed that the MR results were not significantly affected by single SNP leave-out ] analyzed by using the IVW method, while the weighted median showed a positive effect . Since there was heterogeneity  and a lack of directional pleiotropy , according to We further investigated the relationship between waist circumference and the risk of POAG by MR analysis . The resp = 0.00305; adjusted P = 0.00645)]. The weighted median results also confirmed this relationship . To assess the stability and reliability of these results, a sensitivity analysis was performed. The heterogeneity test showed that there were no heterogeneities , and the directional pleiotropies tested by using the MR–Egger intercept also showed that there were no pleiotropies . Finally, the leave-one-out test indicated that the MR results were stable and were not significantly affected by single SNP leave-out  ], , and , respectively}. The causal relationships between BMI, hip circumference, and POAG were primarily analyzed by using the IVW method, and the sensitivity analysis revealed that there were no heterogeneities or pleiotropies. However, the causal association between waist circumference and POAG assessed by IVW suggested a null result. Since there was pleiotropy presence, the results analyzed by weighted median were adopted according to a previous study and showed a positive effect on POAG. This might be attributed to the database used in this study, and this result should be interpreted cautiously.In traditional observational epidemiological studies, confounders often interfere with the results, which makes the explanation of etiology unreliable. Mendelian randomization is an epidemiological research design and data analysis based on Mendelian independent distribution law, which is an unbiased estimation of causal effects . In addiAt present, there are some hypotheses about the mechanisms of how obesity increases the risk of POAG. On the one hand, too much adipose tissue might increase the pressure of the scleral vein and blood viscosity, improve the outflow resistance in the scleral vein, and cause a decrease in intraocular blood perfusion . On the Our study has some strengths: 1) We first assessed the causal relationship between obesity and POAG by MR analysis, in which confounders and biases could be largely eliminated. 2) BMI, waist circumference, and hip circumference were chosen as exposures to perform two-sample MR, which could comprehensively evaluate these causal effects. There were also some limitations in this study: 1) The two-sample MR analysis was based on a European ancestry, and this relationship might change in individuals of other ancestries; a two-sample MR analysis of individuals of at least one other ancestry should also be performed. 2) This study, which uses only summary statistics for MR analysis, could make only a preliminary judgment on the causal relationship between obesity and POAG, and the specific mechanisms of how obesity increases the risk of POAG still need further research.In conclusion, our principal findings revealed that genetically predicted BMI, waist circumference, and hip circumference were related to the risk of POAG. To our knowledge, the present study performed a two-sample MR study for the first time to investigate the causal effect of obesity on POAG. To the best of our knowledge, this was the first study to investigate the causal effect of obesity on POAG, and our results further confirmed that obesity could increase the risk of POAG, which might provide guidance on the prevention and treatment of POAG.


Prior studies have shown that greenness can reduce the burden of depressive disorders. However, most were focused on local-scale analyses while limited evaluated globally. We aimed to investigate the association between greenness and the burden of depressive disorders using data from 183 countries worldwide.We used the normalized difference vegetation index (NDVI) to estimate greenness. Country-level disability-adjusted life year (DALY) loss due to depressive disorders was used to represent depressive disorder burdens. A generalized linear mixed model was applied to assess the relationship between greenness and depressive disorders after controlling for covariates. Stratified analyses were conducted to determine the effects of greenness across several socio-demographic levels.The findings showed a significant negative association between greenness and the health burden of depressive disorders with a coefficient of −0.196  in the DALY changes per interquartile unit increment of NDVI. The stratified analyses suggested beneficial effects of greenness on depressive disorders across sex, various age groups especially for those aged <49 years, with low-income and/or those living in highly urbanized countries.Our study noted that greenness exposure was significant negative association with the burden of depressive disorders. The findings should be viewed as recommendations for relevant authorities in supporting environmental greenness enhancement to reduce the mental burdens. Mental illness is one of the most widespread and devastating global problems . The impOver time, related issues in the economy, education, and wealth have made socioeconomic status an important focus leading to individual mental health problems, such as depression . PreviouAlthough previous studies have investigated the positive effect of greenness on depressive disorders such as major depressive disorder and dysthymia, most were only focused on local-scale analyses while limited available studies have evaluated the benefits of greenness globally. Knowing that depressive disorders is a pioneer for global psychological burden, in this ecological study, we proposed a novel concept to investigate the association between greenness and the burden of depressive disorders in 183 countries worldwide. The main aimed was to respond to scientific gaps related to the relationship between green exposure and mental health burden, which is mostly only carried out in developed countries. By evaluating the association using multinational data, this study proposed to cover the shortfall in evaluating the relationship between greenness exposure and the burden of depression globally, which includes developed and developing countries. We hypothesized that exposure to greenness is inversely associated with the health burden due to depressive disorders globally. We also hypothesized that the beneficial effects of greenness on depressive disorders varies by age, sex, economic status, and urbanization level. Finally, for this study we focused on population-based proxies, therefore the related findings could serve as a baseline for global studies that support environmental development to improve the quality of health and wellbeing.www.who.int/healthinfo/global_burden_disease/estimates/en/index1.html). This data is an estimated value and calculated from a combination of medical data, epidemiology, survey, and meta-regression modeling for each country. In brief, DALY is a summary metric of population health burden due to specific disease. It includes two components: years lived with disability (YLD) and years of life lost due to premature mortality (YLL). This data used a new normative standard life table to compute YLL and adjusted for comorbidity to calculate YLD (We used the data for disability-adjusted life years (DALY) loss to represent the country-level disease burden due to depressive disorders. This data was provided by the World Health Organization (WHO) from the Global Burden of Disease (GBD) study database. Country-level annual estimation data were available for the four follow-up years   measured by a Terra Moderate Resolution Imaging Spectroradiometer (Terra-MODIS) sensor with 1x1 km spatial resolution was used to estimate the presence of greenness in each country . The datIn all, this process integrated a total of 4,672 images across the four follow-up years . The spatial distribution of greenness in each country based on the NDVI estimations is shown in 2.5) estimation with spatial resolution 1 × 1 km2 provided by The Atmosphere Composition Analysis Group, Dalhousie University . This is because recent studies confirmed the negative effects of PM2.5 on mental health , demographic factors , economic status, the prevalence rate of education level, urbanization level, the prevalence rates of populations without religion, divorce rate, lifestyle behaviors , blood pressure, healthcare expenditure, and meteorological factors .Descriptive statistics were provided to present the country-level characteristics of all covariates examined in this study, including DALY loss of depressive disorders, environmental exposures  were applied to examine the multicollinearity problem across covariates  with a penalized quasi-likelihood (PQL) algorithm to determine the relationship between exposure to greenness and the health burden of depressive disorders. The GLMMPQL accounts for both fixed and random effects and provides a flexible approach for analyzing health outcomes . In the variates , 49. Thevariates .Model 1 only includes greenness exposure; Model 2 includes exposure to greenness and PM2.5 exposure; Model 3 adds education and economic status in addition to exposure to greenness and PM2.5 exposure; Model 4 adds urbanization level and the prevalence rate of the population without religion; Model 5 adds behavior factors; and Model 6 considered blood pressure as a risk factor and divorce rates for each country. In this sensitivity analysis, we assumed that there is no significant change in the estimation coefficient or the significance indicator  which indicates the robustness of the main relationship model.To evaluate the robustness of our main association model, a sensitivity test was applied. We included different covariates in six separate models adjusted by population density, age, sex, and year in order to discern the change in coefficient estimation and significance. Specifically, Subsequently, this study conducted stratified analysis based on the level of greenness and socio-demographic factors. First, by using quartile of NDVI (Q1–Q4), the association between greenness in different exposure levels and the burden of depressive disorders were examined. In this case, Q1 represented countries with lower exposure to greenness (as reference), and Q4 represented countries with higher exposure to greenness, quartile 1 (NDVI: 0.085–0.389); quartile 2 (NDVI: 0.390–0.524), quartile 3 (NDVI: 0.525–0.622), and quartile 4 (NDVI: 0.623–0.808). This stratified analysis was considered, given that not all countries have the same green exposure. By completing this analysis, it can be seen whether there is a difference in the effect of the level of green exposure on the outcome. Second, the association between greenness and depressive disorder burdens was examined in different level of socio-demographic factors . In this2.5 exposure and burden of IHD. A prior study confirmed that PM2.5 was correlated with an increased risk of depressive disorder burdens  and replacing health burden  with other disease burdens from the same dataset could yield consistent results. For positive outcome control, we evaluated the linkage between greenness and the burden of disease due to cardiovascular diseases and for negative outcome control we evaluated Human Immunodeficiency Virus or HIV. Cardiovascular diseases were chosen as a positive outcome control because Yeager's study showed that greenness has a beneficial impact on reducing cardiovascular risk . HIV was burdens . Then, wp < 0.05 were considered statistically significant. Further, to avoid false discovery rate for independent test statistics, adjusted p-value  was then calculated using the more powerful adjustment method proposed by Benjamini and Hochberg  and R version 3.6.3 . Coefficient estimates with 95% confidence intervals (CI) were reported and Hochberg  and JafaHochberg .2.5 exposure was 19.45 μg/m3 (SD: 16.10 μg/m3); the population density of all selected countries was about 163 population per km2 (mean ± SD: 163.37 ± 722.47 persons); and almost 50.0% of the global population measured was female.A significant negative association between global greenness and depressive disorder burdens were observed , with a p > 0.05) were found in the developed models.In a detailed assessment, the coefficient estimates for all associated risk factors adjusted in the models were presented in After adjusting for potential risk factors, the stratified analyses by sex, age group, economic status, and urbanization level were assessed . We foun2.5), a positive exposure control, and depressive disorders. Second, the relationship between the health burden of depressive disorders and wind speed, a negative exposure control, was not significant. We also examined associations between exposure to greenness and positive or negative outcomes. A significant relationship between greenness and cardiovascular diseases, a positive outcome control, was found, whereas a non-significant relationship between greenness and HIV, a negative outcome control, was also observed.The results of the associations between positive or negative exposures and depressive disorder burdens were shown in To our knowledge, this is the first global ecological study to investigate the association between greenness and the health burden of depressive disorders across multiple countries. Consistent with our hypotheses, our findings showed a significant negative association between greenness and depressive disorder burdens. In various sensitivity analyses, we consistently obtained similar results and supportive evidence that the higher the greenness exposure, the lower the health burden due to depressive disorders. The significant negative association of exposure to greenness with the burden of depressive disorders remained after accounting for potential country-level risk factors.p = 0.004)  . In Amer= 0.004) . Taking = 0.004) . Moreove= 0.004) . Applyin= 0.004) . Further= 0.004) . Support= 0.004) –68. The = 0.004) ; maligna= 0.004) , 70; dia= 0.004) , 72; res= 0.004) , 74; and= 0.004) . In geneHow the presence of greenness could have a significant negative association with the burden of depressive disorders was explained by several plausible reasons. Ulrich  emphasizWe did not find a sex difference in the association between greenness and the burden of depressive disorders. In support of our findings, a systematic review by Bolte et al. showed that no consistent sex differences have been shown related to the impact of greenness on health . We did Several strengths were noted in this study. This is the first global ecological study to investigate the association between greenness and the health burden of depressive disorders across 183 countries worldwide. Thus, our findings can serve as a global baseline for future environmental development research studies. Our methodological considerations were sound and included the use of various spatial-statistical approaches to deal with the spatial autocorrelation issue that may be caused by clustering patterns. Moreover, we adjusted our analytical models for several potential confounders with influence on the effectiveness of greenness in minimizing the burden of depressive disorders.Some limitations also need to be acknowledged. Recognizing that the DALY data provided by WHO is only available at the country-level, not available at the state and/or city levels. A distinct analysis for big countries within-country variability cannot be done. Coming studies could examine the effects of greenness benefits at local communities in the case a finer-resolution DALY data available. In addition, the health burden data represented by DALY obtained from the Global Burden of Disease (GBD) study is multinational and multitemporal data that can be updated. Knowing this issue, considering the latest DALY data is recommended. Although we used greenness data for the same period as the main outcome, due to the limited accessibility of vegetation species data for each country, we did not adjust for the effects of biodiversity in the models. We only used NDVI value to represent total greenness exposure and assumed that all types of greenery had a positive impact on health. In the case of land use or land cover data showing the diversity of greenness is available on a global scale or other green index derived from satellite could estimate spatial greenness exposure, perhaps this could be a better consideration for future studies. Some related factors are unavailable in the global datasets, such as genetic or hereditary disease, health care quality index and ethnicity and/ or race. It will be important to explore the effects of these important factors on depressive disorders in future studies. This study also used an ecological study design, and the measure of exposure was only proxy-based on the average of the whole population. We recognize that the lack of individual data might have some impact on the strength of evidence provided by this study. Finally, the results of this global analysis cannot be directly compared to observational studies and the results should be interpreted with caution.Our findings demonstrate a significant negative association between exposure to greenness and the burden of depressive disorders, particularly in low-income and high-urbanized countries. This study is the first to provide evidence for the link between greenness and depressive disorder burdens on a global scale. The findings from this study should serve as a call to policymakers and communities to deploy environmental interventions in terms of helping to deal with the global health burden of depressive disorders, with the potential for positive repercussions for the world.The original contributions presented in the study are included in the article/AKA, S-CCL, H-JS, C-DW, and JDS: conceptualization. AA, H-JT, W-CP, YLG, and C-DW: methodology. AKA and W-CP: formal analysis. AKA, H-JT, and C-DW: writing—original draft preparation. AKA, H-JT, W-CP, YLG, C-PY, C-SW, H-JS, S-CCL, C-DW, and JDS: writing—review and editing. C-DW, S-CCL, and H-JS: supervision and funding acquisition. All authors contributed to the article and approved the submitted version.This study was funded by Academia Sinica, Taiwan, under Trans-disciplinary PM2.5 Exposure Research in Urban Areas for Health-oriented Preventive Strategies (II) (Project No.: AS-SS-110-02).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The presence of reward deficits in major depressive disorder is associated with abnormal striatal function. However, differences in striatal whole-brain functional between recurrent depressive episode (RDE) and first-episode depression (FDE) have not been elucidated. Thirty-three patients with RDE, 27 with FDE, and 35 healthy controls (HCs) were recruited for this study. A seed-based functional connectivity (FC) method was used to analyze abnormalities in six predefined striatal subregion circuits among the three groups of subjects and to further explore the correlation between abnormal FC and clinical symptoms. The results revealed that compared with the FDE group, the RDE group showed higher FC of the striatal subregion with the left middle occipital gyrus, left orbital area of the middle frontal gyrus, and bilateral posterior cerebellar gyrus, while showing lower FC of the striatal subregion with the right thalamus, left inferior parietal lobule, left middle cingulate gyrus, right angular gyrus, right cerebellum anterior lobe, and right caudate nucleus. In the RDE group, the HAMD-17 scores were positively correlated with the FC between the left dorsal rostral putamen and the left cerebellum posterior lobe. This study provides new insights into understanding the specificity of striatal circuits in the RDE group. Major Depressive Disorder (MDD), as a common clinical psychiatric disorder, causes great distress to patients . EpidemiBoth FDE and RDE are clinically common subtypes of MDD, but their clinical symptoms may differ . PreviouResting-state functional magnetic resonance imaging (rs-fMRI) is an effective tool for studying psychiatric disorders, including MDD ,12, autiIn addition, we found that neurological dysfunction in MDD patients also focused on abnormalities in the cortico-striato-thalamo-cortical (CSTC) circuit ,27. The However, only one previous study on striatal aspects of MDD at different stages found that increased caudate-insular and reduced VS-cerebellar FC in remitted patients and first-degree relatives might be related to the disease itself and have potential for predicting risk for and recurrence of MDD . Two othTherefore, we used FC to observe the difference in brain functional activity between RDE and FDE in striatal subregions and further observed the correlation between FC abnormalities and clinical symptoms. This study will contribute to the understanding of neuroimaging markers for the onset and progression of MDD at different disease stages, and provide some insights into the differences between RDE and FDE in terms of reward network activity.In this study, MDD patients were sourced from Guang’anmen Hospital, China Academy of Chinese Medical Science, Beijing First Hospital of Integrated Chinese and Western Medicine. Patients underwent a psychiatrist with extensive clinical experience for inclusion. Sixty patients with MDD were included according to the Diagnostic and Statistical Manual of Mental Disorders Fifth Edition criteria. The severity of the MDD patients recruited was generally moderate to severe. The inclusion criteria met the following : (1) 17-The exclusion criteria for all subjects were as follows : (1) conAll subjects underwent MRI  scans at the Department of Radiology, Guang’anmen Hospital, China Academy of Chinese Medical Sciences. The subjects were instructed to keep their eyes closed and remain quiet and awake during the scan. A T2-weighted MRI plain scan was first performed to exclude organic brain lesions. Functional brain MRI data acquisition method: 3D T1-weighted imaging scan first, with the following parameters: time repetition (TR) = 2530 ms, time echo (TE) = 2.98 ms, field of view (FOV) = 256 mm × 256 mm, slice number = 48, slices = 192, flip angle (FA) = 7°, slice thickness = 1 mm, scanning time = 6 min 3 s. The blood oxygen level dependent (BOLD) sequence collects functional data with the following parameters: TR = 2000 ms, TE = 30 ms, FA = 90°, FOV= 240 mm × 240 mm, matrix = 64 × 64, number of obtained volumes = 200, slice thickness/spacing = 3.0/1 mm, scanning time = 6 min 40 s.http://www.rfmri.org/DPARSF, accessed on 15 September 2022) [Data preprocessing was performed on rs-fMRI data based on MATLAB 2020a using the DPARSF 5.0 toolkit  , with th3 space (radius = 4 mm). These six predefined striatal partitions are shown in detail in The selection of seed point coordinates in the striatal subregion was based on previous studies ,38,42. SThe mean time series of all voxels in the ROI were extracted and calculated for each subject, and Pearson correlation analysis was done with the time series of whole-brain voxels to obtain a map of functional connectivity between the region of interest and the whole brain. The functional connectivity values were expressed as correlation coefficients, which were then transformed into Z values by Fisher’s Z-transformation to conform to a normal distribution.t-test was used to compare HAMD-17 score, duration of illness between the two patient groups. The statistical threshold was set at p < 0.05 for statistical significance.SPSS 23.0 software  was used to statistically analyze the clinical data. The chi-square test was used to compare sex among the three groups. One-way analysis of variance (ANOVA) tests was used to compare age, yeas of education among the three groups. A two-sample p < 0.05, threshold voxel level p < 0.005 being defined as statistically significant differences. Image data statistics were analyzed using DPARSF 5.0 software , and FC values between the three groups were analyzed using one-way ANOVA with sex, age, yeas of education and mean framewise displacement (FD) of the subjects among the three groups as covariates, and Gaussian random fields (GRF) correction was applied to the brain areas with differences in FC among the three groups, with cluster level p < 0.016 (0.05/3). Pearson correlation analysis was performed between the FC values of the three differential brain regions and HAMD-17 scores, and statistical significance was defined at p < 0.05.The mean FC values of the abnormal brain areas in the three groups were extracted using DPARSF software, and the results obtained were subjected to Bonferroni correction using SPSS 23.0 for post hoc two-group comparisons , and the differences were defined as statistically significant at In this study, we did not find subjects with excessive FD. Thus, a total of 27 patients with FDE, 33 with RDE and 35 HCs met the criteria for this study. There were no statistical differences among the three groups in terms of age, sex, and years of education. In addition, we found no statistical difference between the RDE and FDE groups in terms of HAMD-17 scores, while there were statistical differences in the duration of illness .One-way ANOVA showed that when the right VSi was used as the seed, the left middle occipital gyrus and right cerebellum posterior lobe were statistically significantly different among the three groups A. ComparOne-way ANOVA showed that when the left VSs was used as the seed, the right thalamus and left inferior parietal lobule were statistically significantly different among the three groups B. ComparOne-way ANOVA showed that when the right VSs was used as the seed, the left orbital area of the middle frontal gyrus was statistically significantly different among the three groups C. ComparOne-way ANOVA showed that when the left DC was used as the seed, the left middle cingulate gyrus and left inferior parietal lobule were statistically significantly different among the three groups D. ComparOne-way ANOVA showed that when the right DC was used as the seed, the right angular was statistically significantly different among the three groups E. ComparOne-way ANOVA showed that when the left DCP was used as the seed, the right cerebellum anterior lobe was statistically significantly different among the three groups F. ComparOne-way ANOVA showed that when the left DRP was used as the seed, the right caudate and left cerebellum posterior lobe were statistically significantly different among the three groups G. ComparOne-way ANOVA showed that when the left VRP was used as the seed, the left cerebellum posterior lobe was statistically significantly different among the three groups H. Comparr = 0.409, p = 0.017)  .To our knowledge, this is the first study to analyze differences in striatal whole-brain FC between patients with RDE and FDE. We found FC differences between the RDE and FDE groups in some subregions of the striatum. In addition, the RDE group had more significant alterations in the striatal subregion compared to the HC group. In addition, the HAMD-17 scores were positively correlated with the FC between the left DRP and the left cerebellum posterior lobe in the RDE groupThe primary finding of this study was that patients with RDE and FDE had different FC alterations in striatal subregions  and DMN. The DMN contains inferior parietal lobule and angular gyrus, which are mainly involved in word comprehension, digit processing and situational memory functions ,44,45,46Other studies have also shown FC disorder between striatum and DMN in patients with MDD ,44. A stThe FC of striatal subregions (VSi.R) and left middle occipital gyrus was higher in the RDE group compared to the FDE group. The middle occipital gyrus, which is mainly associated with the processing of linear space in humans, belongs to the visual processing cortex and plays an important role in the pathogenesis of MDD ,51,52. PThe cerebellum is involved not only in motor processes but also in cognitive and emotional regulation . StudiesThe FC of the striatal subregion  with right thalamus, and left middle cingulate gyrus was lower in the RDE group compared to the FDE group. The limbic system is a complex neural network composed of the cingulate gyrus, hippocampus, amygdala, and thalamus that is involved in the generation and expression of emotions in the body, as well as in the formation, storage, and extraction of memories ,61. PrevThe results of this study also found that the FC of the right VSs and the left orbital area of the middle frontal gyrus was higher in the RDE group compared to the FDE group, while the FC of the left DRP and the right caudate was lower. The orbitofrontal cortex and caudate are important components of the reward network which are associated with reward motivation and depression ,64,65. AIn addition, compared with the HC group, we found that the abnormal FC alterations in the striatal subregion were more extensive and deeper in the RDE group than FDE group. Compared with the HC group, a study found more extensive FC changes in striatal subregions in the rMDD group than acute MDD group, suggesting that this may be due to caused by MDD-relieving scars . Anotherp < 0.005. A threshold value of p < 0.001 would be more clinically significant for such a study. In the future, the sample size will be expanded, and a more rigorous correction method will be used to improve the scientific value of this study. Finally, HAMD-17 was only used on one clinical scale in this study. In future studies, clinical scales such as anxiety, insomnia, and redundancy will be used to further observe the correlation between abnormal changes in the RDE and FDE striatal circuits and clinical symptoms.Some limitations of this study should be considered. First, we cannot exclude the potential effect of antidepressant factors on brain function in patients with RDE. Second, some of the RDE patients in this study were not first-time relapses, and a study of first-time relapses in RDE patients may be of more clinical research value. Third, this study used GRF correction with a weaker statistical threshold setting of The results of the present study suggest differences between RDE and FDE patients at the level of striatal circuits, especially related to alterations in the DMN, visual processing cortex, cerebellar sensorimotor network, limbic system and reward network of FC with different striatal areas. This study provides new insights into understanding the specificity of striatal circuits in the RDE group.


With the rapid aging population, the mental health of older adults is paid more and more attention. Anxiety is a common mental health illness in older adults. Therefore, the study aimed to explore the current situation of anxiety and its factors among the elderly in China.Based on the data from 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS), a total of 10,982 respondents aged 60 and above were selected. Generalized Anxiety Disorder (GAD-7) scale was used to assess the anxiety. Univariate and multivariate analysis were used to analyze the influencing factors of anxiety. Random forest was established to rank the importance of each influencing factors.The results showed that the prevalence of anxiety among the elderly was 11.24%. Anxiety was mainly associated with 14 factors from five aspects: sociodemographic characteristics, health status, psychological state, social trust and social participation, among which loneliness related to psychological status was the most important factor.The revelation of this study is that the present situation of anxiety among the elderly cannot be ignored, and it is necessary to take measures to prevent and control it from many aspects. In recent years, many countries around the world have experienced a rapid aging population, which has led to growing concern about the public health issues of elderly individuals, both physical and mental health. Similarly, as a country where the elderly comprise approximately 13.5% of its total population , which is organized by the Center for Healthy Aging and Development Studies (CHADS) of Peking University. Its collection began in 1998 and was followed up in 2000, 2002, 2005, 2008/2009, 2011/2012, 2014, and 2018, covering basic demographic characteristics, social, economic and health aspects. The sampling design of CLHLS adopted a multi-stage disproportionate and targeted random sampling method which makes the sample data representative and reliable . The datAnxiety was used as the dependent variable in this study. Participants’ anxiety was assessed by the 7-item Generalized Anxiety Disorder (GAD-7) scale translated into Chinese language . The scaIn this study, we classified the factors that might be associated with anxiety into 7 aspects: sociodemographic characteristics, lifestyle, health status, psychological state, social trust, social support and social participation. Specifically, the sociodemographic characteristics were as follows: age , gender , occupation , the area of residence , and self-rated economic status(SRE) (1 = very rich to 5 = very poor). Marital status was coded into the following two categories: 0 = not married , 1 = married (married or cohabitating). The form of residence was categorized as “non-alone” (with household member(s) or in an institution) and “alone.” Self-rated quality of life (SRL) and self-rated sleep quality (SRS) were recorded on a five-point scale as follows: 1 = very good; 2 = good; 3 = so-so; 4 = bad; and 5 = very bad.Lifestyle consisted of current smoking status , current drinking status , and current exercise or not .Health status was assessed through seven areas: (1) Self-rated health status (SRH). Self-rated health status was assessed on a five-point scale: 1 = very good; 2 = good; 3 = so-so; 4 = bad; 5 = very bad. (2) Two-week morbidity. Two-week morbidity was evaluated with the following question: “Have you been feeling not-well within the past 2 weeks?” (3) Number of chronic disease. Total number of chronic diseases was grouped as 0, 1 and ≥2 . (4) SenIn terms of psychological state, we applied a question to measure loneliness: “Do you feel lonely?” The scores ranged from 1 to 5, which meant that the lower the scores were, the greater the loneliness. Similarly, social trust was also measured by a five-point question: “Do you often feel that people around you are not trustworthy?” Higher scores indicated better trust in society.Social participation refers to individuals’ reasonable participation in social activities . AccordiRandom Forest is a machine learning method based on a classification tree, which can deal with both classification and regression analysis . The basP < 0.05(two-sided).IBM SPSS Statistics version 24 and RStudio were used for data analysis. First of all, descriptive analysis was performed on the samples. Chi-square test was used for univariable analysis. Secondly, the factors with statistical significance in univariate analysis were included in binary logistic regression to explore the influencing factors of anxiety in the elderly. In addition, RStudio was used to establish the random forest to evaluate and rank the importance of the influencing factors of anxiety. The level of statistical significance was As shown in p < 0.05). In terms of health status, except for ADL disability, the other six factors were significantly related to anxiety (p < 0.05). Regarding social support, only informal social support including intergenerational material and non-material support proved to be linked with anxiety (p < 0.05). This study found that the prevalence of anxiety was 11.24%. Compared with participants without anxiety, participants with anxiety were more likely to be older, female, not married, work in agriculture and live in rural areas. At the same time, the distribution of anxiety among the elderly with different characteristics was obtained by univariate analysis, which indicated that all sociodemographic factors and the variables included in life style, psychological state, social trust and social participation were significantly related to anxiety , this study explored the current situation of anxiety and its influencing factors among Chinese elderly people aged 60 and above. The study found that the prevalence of anxiety was 11.24%, which was consistent with previous studies for Chinese elderly adults . FurtherSelf-rated sleep quality reflects the individual’s subjective perception of their daily sleep, and is also a general indicator widely used in assessment of sleep quality . ResultsAnother interesting finding of this study was that a good sense of social trust could effectively alleviate anxiety among the elderly. In essence, social trust is the embodiment of social relationship. It is a collection of various factors that shape interpersonal relationship, with universality and stability . EmpiricIn addition to the above three most important factors related to anxiety among the elderly, we also found that the impact of health-related factors on anxiety was also noteworthy. The study showed that people with a lower level of self-rated health had a higher risk of anxiety. Similarly, 2-week morbidity, hearing impairment and falls may also cause anxiety. There is evidence that people may fear the potential consequences of poor health status, which would trigger the development of anxiety . As a meThe study also proved that SRL and SRE were linked with anxiety among the elderly (ranked fourth and fifth in terms of importance). SRL and SRE can be regarded as people’s subjective evaluation of the quality of life and economic situation. The negative correlation between quality of life and anxiety has been well confirmed in many studies , 65. PreThe results of this study are based on cross-sectional data, and it is difficult to infer causality, which should be further verified by longitudinal studies. In addition, the study only explored the relationship between loneliness and anxiety. More measures of other psychological state should be introduced in the future. Finally, some variables were evaluated by single or self-reported items. The participants’ subjective awareness may affect the authenticity of the measurement results. In future research, enriching the diversity and objectivity of indicators will better guarantee the quality of the study.In this study, we explored the prevalence of anxiety among elderly people aged 60 and above and analyzed the importance of various influencing factors of anxiety using random forest model. According to the results, loneliness, self-rated sleep quality and social trust had a great impact on anxiety, followed by self-rated health status, self-rated quality of life, self-rated economic status, 2-week morbidity, age, hearing impairment, group activities, gender, marital status, fall and area of residence. Based on this, we call on the whole society to pay attention to the mental health of the elderly. Relevant departments and policy-makers should formulate targeted actions to improve the health literacy of the elderly, such as carrying out health education, providing emotional care for lonely elderly group, encouraging the elderly to participate in social activities and enriching their interpersonal relationship, improving regional infrastructure and increasing social welfare and living standards of elderly individuals. These measures are meaningful to attenuate the impact of negative emotions such as anxiety and maintain the psychological health of the elderly.https://opendata.pku.edu.cn/dataverse/CHADS.Publicly available datasets were analyzed in this study. This data can be found here: The CLHLS has been approved by the research ethics committees of Peking University (IRB00001052-13074). Written informed consent was not required as per local legislation and institutional requirements.SY: conceptualization, validation, and writing — original draft. YL: conceptualization, data curation, formal analysis, and writing — review and editing. YX and XY: formal analysis and writing — review and editing. GM and YW: editing. All authors contributed to the article and approved the submitted version.


Among the three coping mechanisms, avoidant coping had a significant positive moderate correlation with both the presence of anxiety  and the presence of burnout . Meanwhile, coping that was neither approach nor avoidant had a positive weak correlation with the presence of burnout . The prevalence of anxiety and burnout was concerning. Increased anxiety and burnout among students may negatively impact aspects of their personal, professional, and academic lives. Early recognition and preventive measures should be emphasised to prevent negative ramifications.This study aimed to determine the prevalence of anxiety and burnout, and the coping mechanisms among clinical year undergraduate medical students in Universiti Kebangsaan Malaysia (UKM) during the coronavirus disease 2019 (COVID-19) pandemic. In total, 378 clinical year undergraduate medical students in UKM participated in this cross-sectional study from May to July 2021. A self-administered questionnaire consisting of questions on the participant’s sociodemographic data and items from the DASS-21, CBI, and Brief-COPE was distributed. Chi-square and Spearman’s correlation tests were used to calculate the correlation coefficient between both anxiety and burnout, and coping mechanisms. The prevalence of anxiety and burnout were 44.2% and 22.2%, respectively. There was a significant difference in the percentage of students with extremely severe anxiety in the presence and absence of burnout, 23.8% vs. 4.8% ( Anxiety is a psychological and physiological condition, characterized by cognitive, somatic, emotional, and behavioural components. It acts as a protective factor against threatening situations, while burnout entails feelings or experiences of exhaustion, cynicism, and lack of professional efficacy ,2. AnxieResearch focusing on the concept of burnout became more prevalent during the 1970s where researchers investigated a phenomenon resulting from excessive work demands, later known as “burnout”. The sources of burnout can include workload, control, reward, community, fairness, and values. Burnout can result from a mismatch between the individual and the work environment. Burnout is classified into three types, namely which is personal burnout, work-related burnout, and client-related burnout. Personal burnout is defined as the degree of physical and psychological fatigue, and exhaustion experienced by a person regardless of their working status. Work-related burnout measures the same features, which include the physical and psychological fatigue, and exhaustion experienced by the person but perceived as strictly related to his/her work. Client-related burnout measures the degree of physical and psychological fatigue, and exhaustion the person undergoes at work that is related to his/her clients. A “client” is a broad concept covering patients, children, students, and residents .The theoretical framework for this study was based on the cognitive theory of coping developed by Folkman and Lazarus. This theory was selected because it links the constructs central to this study. Coping was defined as a change in cognitive and behavioural efforts to manage specific external and/or internal demands that are seen as exceeding the resources of the person. This important theory says that an individual’s knowledge acquisition can be directly related to observing others’ examples in social interactions, media influences, and experiences. Coping is a survival technique because it is a result of replicating others’ actions. There are three meta-theoretical assumptions: transaction, process, and context. Lazarus and Folkman’s transactional model describes the interaction between the individual and the stressful event, which is particularly obvious in the individual’s assessment of the problem being faced. According to this interactive model, the individual goes through two different processes which are important to the outcome of the problem. The first is the cognitive assessment, which refers to the way the situation relates to the individual. The second refers to how to deal with the problem .In our study, we evaluated the coping mechanisms used by clinical year medical undergraduate students in the presence or absence of anxiety and burnout during the COVID-19 pandemic by using the Brief-COPE (Coping Orientation to Problems Experienced) tool. For our study, coping refers to the process by which a student successfully manages stressful events that are seen as exceeding the available resources. The Brief-COPE tool is the abbreviated version of the COPE Inventory and assesses dispositional as well as situational coping efforts. The inventory is the tool most widely used to measure coping. It is a shortened version of the full 60-item  COPE inventory developed by Carver et al. . The 28-The measurement models of Brief-COPE can group the 14 subscales into two-category or three-category models . In our The UKM Doctor of Medicine (MD) undergraduate course aims to produce well-rounded medical professionals who can serve society in varied work environments and who are well-positioned for further postgraduate training. Before the pandemic began, the UKM undergraduate medical course’s structure included ward rounds, tutorials, lectures, and seminars to nurture skills in problem solving, methods of inquiry, critical thinking, and independent learning strategies ,10.During the COVID-19 pandemic, the teaching and learning (T&L) methods were adapted to the current circumstances. Digital learning and clinical experience simulation software were introduced to help the students continue their studies despite restricted entry to clinics, wards, and academic buildings. Digital learning is a process of integrating technology-mediated synchronous and asynchronous approaches including assessments, assignments, and tutoring, and it enables learning without any time and location restrictions. The migration of face-to-face learning to synchronous or asynchronous digital learning with a period of transition and adaptation, was associated with challenges such as poor connectivity and a lack of the knowledge, tools, and infrastructure .The medical students faced difficulties in adapting to the “new normal”, e.g., the nationwide quarantine measures, the faculty’s digital learning initiative, and reduced clinical exposure . The panWith this background, this study aimed to determine the prevalence of anxiety and burnout, and the associations between anxiety and burnout, between anxiety and the coping mechanisms implemented, and between burnout and the coping mechanisms implemented in UKM’s clinical year undergraduate medical students amidst the COVID-19 pandemic. We hypothesized that the anxiety level among clinical year medical undergraduate students would be higher compared with pre-clinical year medical undergraduate students. Therefore, the clinical year medical undergraduate students were selected for this study. We hoped to obtain baseline information regarding anxiety, burnout, and coping mechanisms among the clinical year undergraduate medical student through our study. The result from this study might be helpful for future research or randomized controlled trials with better interventions.A cross-sectional study was conducted among clinical year undergraduate medical students in the Faculty of Medicine, UKM. The study was carried out between May and July 2021 during the 2020/2021 academic session. This population group was selected because limited data have been collected on clinical year undergraduate medical students who are studying in Malaysia. All clinical year undergraduate medical students (Year 3 to Year 5) who gave consent were included in this study. The exclusion criteria were incomplete questionnaires and those diagnosed to have an anxiety disorder(s) prior to the COVID-19 pandemic. Self-administered questionnaires and informed consent forms were distributed during face-to-face sessions.n1) was estimated to be 344.A universal sampling method was used In this study, and the sample size was calculated using Kish’s  formula n) of 378 was needed to adequately estimate the population’s prevalence with good precision.With the expected response rate set at 90%, this was further inflated by 10% to accommodate any missing data. After calculation, a sample size , the Copenhagen Burnout Inventory (CBI), and the Brief Coping Orientation to Problems Experienced (Brief-COPE) inventory. Anxiety can be categorised into be mild, moderate, or severe by using the DASS-21. There were 21 questions in total, which consisted of components for the three domains, namely depression, anxiety, and stress. The items have responses in terms of frequency along a 4-point Likert scale. The responses were then added to produce a total score for the scale . The CBIα = 0.74 and 0.85, respectively [α = 0.85–0.87 and 0.83–0.87, respectively [The English and Malay versions of DASS-21 have good Cronbach’s alpha coefficients for anxiety, namely ectively ,28. The ectively ,29. Brieectively ,30.p-values less than 0.05 were considered to be significant for all analyses in this study.All the data collected were cleaned and analysed using Statistical Package for Social Sciences (SPSS) Version 26. A descriptive analysis was performed to describe the sociodemographic characteristics, psychological distress, and coping mechanisms implemented by the respondents. Further analysis using the Chi-square test was used to examine the association between anxiety and burnout. Meanwhile, Spearman’s correlation test was conducted to delineate the association between coping strategies and psychological distress. This study was carried out in accordance to the ethics of clinical research, where the autonomy, integrity, and safety of the study subjects were guaranteed. Information sheets consisting of an explanation of the study’s objectives and the informed consent form were obtained from all respondents prior to completing the questionnaire. All data retrieved were kept confidential and anonymous. Due to this, the researchers chose not to communicate with participants who were at risk of or who were experiencing anxiety and/or burnout. Instead, the researchers chose to convey information on the recognition of anxiety and burnout, and a non-exhaustive list of resources to seek help from to the participants. This was achieved via a pamphlet, which was distributed along with the questionnaire itself. This was to avoid any breach of confidentiality, as emphasised. The study was conducted with the ethical approval given by the Research and Ethics Committee of UKM (UKM.FPR.SPI 800-2/27). We hereby declare that this study reflects the authors’ own research and analysis in a truthful and complete manner.n = 378) participated and fulfilled the inclusion criteria. The demographic characteristics of the final survey respondents are summarized in n = 250) of the respondents were female students, while 33.9% (n = 128) were male students. Their ages ranged between 21 and 26 years . By year of study, 36.8% (n = 139) of them were Year 3 students, 29.6% (n = 112) were Year 4 students, and 33.6% (n = 127) were Year 5 students.Out of the 455 clinical year undergraduate medical students in UKM, 83.1% (n = 167) and 22.2% (n = 84).In n = 71) and 41.6% (n = 35), respectively, compared with Year 4 and Year 5 undergraduate medical students in UKM. With regards to gender, more female students reported significant anxiety, 67.0% (n = 112) and burnout 70.2% (n = 59) compared with male students: 33.0% (n = 55) and 29.7% (n = 25), respectively.In According to n = 20) vs. 4.8% (n = 14), with a p-value < 0.001.According to r value of <0.20 was considered as a weak correlation, an r value of 0.2 to 0.8 was considered as a moderate correlation, and r > 0.8 was considered as a strong correlation. Among the three types of coping mechanisms, avoidant coping showed a significantly positive moderate correlation with the presence of anxiety (p < 0.001) and the presence of burnout (p < 0.001). Meanwhile, students who applied neither approach nor avoidant coping mechanisms also had a significant correlation with the presence of burnout with a p-value of 0.001; however, this correlation is a positive weak correlation.Because of the nonparametric distribution of the data, the association between the scores of the coping mechanisms and psychological distress was determined using Spearman’s correlation test in n = 167), while the prevalence of burnout among the students was 22.2% (n = 84), with female students reporting higher levels of anxiety and burnout compared with their male counterparts. Our research finding is supported by many emerging studies in the literature, revealing differences based on gender, where women show higher levels of anxiety in response to the COVID-19 pandemic [n = 9), this is a steep increase and may be attributed to several factors [In this study, the prevalence of anxiety among the clinical year medical undergraduate students was 44.2% , some common factors that might add to anxiety and stress levels during a pandemic include concern about the risk of being exposed to the virus, lacking access to the tools and equipment needed to accommodate digital learning, feelings of guilt about not being on the frontline, uncertainty about the future, learning new communication tools, dealing with technical difficulties, and adapting to a different learning space and/or class schedule .Factors influencing the students’ anxiety could also be related to the COVID-19 stress scale (CSS), which identified five factors of stress and anxiety symptoms related to the COVID-19 pandemic. They include fears of danger and contamination, fears about economic consequences, Coronavirus-related xenophobia, compulsive checking and reassurance seeking, and traumatic stress symptoms .For UKM’s clinical year medical undergraduate students, transitioning from more conventional methods of learning to digital learning also required certain prerequisites. Students who lacked the elements to accept the migration of their medical education to digital learning, and whose medical training through clinical rotations was suspended became increasingly weary of their level of preparedness, leading to increased levels of anxiety.Some factors affecting the level of preparedness included a nonconducive environment for digital learning such as unstable internet access . Some students may lack electronic devices with adequate processing power and hardware that can handle the hours of learning, the demands of running video conferences or running multiple applications and browsers at a time, and so on. On top of that, students were also required to learn to navigate and troubleshoot issues when using certain software as well as hardware  to have the most positive experience in class . ExperieAnother factor for the increased level of anxiety could be related to regular social media use during the pandemic, where the high daily rates of new cases and deaths, and the information and misinformation overload via social media could lead to the development of anxiety and mood disorders. Moreover, students probably had increased screen time in conjunction with the migration to digital learning. Students tended to spend more time on electronic devices, and hence were more prone to social media exposure. The social panic caused by COVID-19 and the public health emergency measures may have led to anxiety, alongside a series of other negative effects such as insecurity, emotional isolation, stigmatisation, and economic loss ,40,41,42Considering the students holistically, there was also the aspect of economic changes in the context of the pandemic. According to the Department of Statistics Malaysia (DOSM), an unemployment rate of 5.3% was reported in May 2020 during the pandemic, compared with 3.3% in 2019 before the pandemic. The impacts of COVID-19 on Malaysia’s economy can also be seen via the depreciation in the Malaysian Ringgit against USD . In UKM,Psychological distress could also be due to the quarantine and lockdown measures. These measures might cause significant changes to students’ social network behaviour and mental health, e.g., increased social media exposure, internet addiction, poor sleep quality, increased loneliness, and a sense of estrangement from family and peers. Students might also experience increased family conflicts from needing to communicate with their families more often at close quarters when quarantining at home .n = 84) was less than before the pandemic, according to data from a study in Universiti Sains Malaysia  during the pre-pandemic period as a comparison [The overall level of burnout during the pandemic  compared with Year 4  and Year 5 students . Year 3 students also reported higher levels of anxiety  compared with Year 4  and Year 5 students . This could be due to the students developing better coping skills over the years. It could also be due to the Year 3 students undergoing a major adaptation to the intense clinical responsibility. Furthermore, the Year 4 and Year 5 students had gone through their psychiatry posting, which could have given them better awareness and insights into mental health issues, and helped instil healthier attitudes in them [In this study, Year 3 medical students reported higher levels of burnout . In the late 1990s, researchers began to suggest a link between anxiety and burnout. Some factors contributing to this association could be an individual’s personality traits, where low extroversion and emotional instability could affect an individual’s tendency to burn out. It was also reported that low extroversion is positively correlated with anxiety, while emotional instability has been shown to be positively related to the core component of burnout, i.e., emotional exhaustion, and depersonalization. Individuals who are more extroverted and more emotionally stable are less likely to develop burnout and vice versa [In this study, there was a significant number of participants with extremely severe anxiety and burnout concurrently . Avoidant coping has been previously linked to anxiety, whereas active and problem-focused strategies have been associated with better health outcomes [Avoidant coping mechanisms showed a significant positive moderate correlation with the presence of anxiety (outcomes .n = 217) of the participants [On the other hand, stressful environments are closely related with poor mental health, physical illness, mediocre performance, and substance abuse. One of the most worrying phenomena is substance abuse among health care practitioners (HCP), as seen in a study from the United Kingdom . Substanicipants ,62. DespStudents who applied avoidant coping mechanism during the COVID-19 pandemic showed a significant positive moderate correlation with the presence of burnout. This result was reflected by a study on UK doctors, where avoidant coping mechanisms  were more frequently used by those suffering from burnout. This suggests that avoidant coping mechanisms significantly contribute to the development of burnout ,64.p < 0.001, r = 0.198). This was reflected by a study on correctional officers in offender centres in the US, where humour was related to an increased level of emotional exhaustion and depersonalisation, both of which are components related to burnout [There was also a significant positive weak correlation between neither approach nor avoidant coping mechanisms and the presence of burnout. However, upon a detailed analysis on individuals using neither approach nor avoidant coping mechanisms, it was found that the coping mechanism of humour had a positive weak correlation with the presence of burnout ( burnout .In general, problem-focused coping is the best coping mechanism. This is because it removes the root problem of the stressor and finds a long-term solution to the problem. However, not all problems can be coped with by using problem-focused coping. This is when emotion-focused coping plays a role, such as acceptance of the situation .The prevalence of anxiety and burnout was concerning. Increased anxiety and burnout among students may negatively impact aspects of their personal, professional, and academic lives. The findings of this study can be used by the academic or faculty administrators for the implementation and improvement of preventive measures specifically for anxiety and burnout among medical students in order to eliminate or minimize the unwanted consequences of anxiety and burnout on physical and mental health, social development, competency, and academic performance among medical students. Early recognition, coping skills, and preventive measures should be emphasised to faculty members and students as a joint effort to prevent the negative ramifications.The use of self-reporting questionnaire has limitations, as they are subject to method variance effects and response biases, such as socially desirable responding. The results of this study are also limited to the clinical year medical undergraduate students from UKM; therefore, the results cannot be generalized to a larger population. Furthermore, this study was limited in its monitoring and reporting aspects. Because of the ethical considerations and the current circumstances of this study, intervention was difficult without compromising the anonymity of the participants.It is important to provide students with a holistic medical education emphasizing positive coping mechanisms and building resilience, on top of competency in the clinical skills . Student