Mental Illness Diagnoses May Not Cause All Mental Symptoms: A Simulation Study for Major Depressive Episodes, Dysthymic Disorder, and Manic Episodes.

Objectives This study aims to understand the statistical significance of the associations between diagnoses and symptoms based on simulations that have been used to understand the interpretability of mental illness diagnoses. Methods The symptoms for the diagnosis of major depressive episodes, dysthymic disorder, and manic episodes were extracted from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR, American Psychiatric Association, Philadelphia, Pennsylvania). Without real-world symptom data, we simulated populations using various combinations of symptom prevalence and correlations. Assuming symptoms occurred with similar prevalence and correlations, for each combination of symptom prevalence (0.05, 0.1, 0.3, 0.5, and 0.7) and correlation (0, 0.1, 0.4, 0.7, and 0.9), 100 cohorts with 10,000 individuals were randomly created. Diagnoses were made according to the DSM-IV-TR criteria. The associations between the diagnoses and their input symptoms were quantified with odds ratios and correlation coefficients. P-values from 100 cohorts for each combination of symptom prevalence and correlation were summarized. Results Three mental illness diagnoses were not significantly correlated with their own symptoms in all simulations, particularly when symptoms were not correlated, except for the symptom in the major criteria of major depressive episodes or dysthymic disorder. The symptoms for the diagnosis of major depressive episodes and dysthymic disorder were significantly correlated with these two diagnoses in some simulations, assuming 0.1, 0.4, 0.7, or 0.9 symptom correlations, except for one symptom. The overlap in the input symptoms for the diagnosis of major depressive episodes and dysthymic disorder also leads to significant correlations between these two diagnoses, assuming 0.1, 0.4, 0.7, and 0.9 correlations between input symptoms. Manic episodes are not significantly associated with the input symptoms of major depressive episodes and dysthymic disorder. Conclusion There are challenges to establish the causation between psychiatric symptoms and mental illness diagnoses. There is insufficient prevalence and incidence data to show all psychiatric symptoms exist or can be observed in patients. The diagnostic accuracy of symptoms to detect a disease cause is far from perfect. Assuming the symptoms of three mood disorders may present in patients, three diagnoses are not significantly associated with all psychiatric symptoms used to diagnose them. The diagnostic criteria of the three diagnoses have not been designed to guarantee significant associations between symptoms and diagnoses. Because statistical associations are important for making causal inferences, there may be a lack of causation between diagnoses and symptoms. Previous research has identified factors that lead to insignificant associations between diagnoses and symptoms, including biases due to data processing and a lack of epidemiological evidence to support the design of mental illness diagnostic criteria.

Characterization of chicken-derived antibody against Alpha-Enolase of Streptococcus pneumoniae.

Streptococcus pneumoniae is a clinically relevant pathogen notorious for causing pneumonia, meningitis, and otitis media in immunocompromised patients. Currently, antibiotic therapy is the most efficient treatment for fighting pneumococcal infections. However, an arise in antimicrobial resistance in S. pneumoniae has become a serious health issue globally. To resolve the problem, alternative and cost-effective strategies, such as monoclonal antibody-based targeted therapy, are needed for combating bacterial infection. S. pneumoniae alpha-enolase (spEno1), which is thought to be a great target, is a surface protein that binds and converts human plasminogen to plasmin, leading to accelerated bacterial infections. We first purified recombinant spEno1 protein for chicken immunization to generate specific IgY antibodies. We next constructed two single-chain variable fragments (scFv) antibody libraries by phage display technology, containing 7.2 × 107 and 4.8 × 107 transformants. After bio-panning, ten scFv antibodies were obtained, and their binding activities to spEno1 were evaluated on ELISA, Western blot and IFA. The epitopes of spEno1 were identified by these scFv antibodies, which binding affinities were determined by competitive ELISA. Moreover, inhibition assay displayed that the scFv antibodies effectively inhibit the binding between spEno1 and human plasminogen. Overall, the results suggested that these scFv antibodies have the potential to serve as an immunotherapeutic drug against S. pneumoniae infections.

The Upper Limits of Risk Ratios and Recommendations for Reporting Risk Ratios, Odds Ratios, and Rate Ratios.

Background Relative measures, including risk ratios (RRs) and odds ratios (ORs), are reported in many epidemiological studies. RRs represent how many times a condition is likely to develop when exposed to a risk factor. The upper limit of RRs is the multiplicative inverse of the baseline incidence. Ignoring the upper limits of RRs can lead to reporting exaggerated relative effect sizes. Objectives This study aims to demonstrate the importance of such upper limits for effect size reporting via equations, examples, and simulations and provide recommendations for the reporting of relative measures. Methods Equations to calculate RRs and their 95% confidence intervals (CIs) were listed. We performed simulations with 10,000 simulated subjects and three population variables: proportions at risk (0.05, 0.1, 0.3, 0.5, and 0.8), baseline incidence (0.05, 0.1, 0.3, 0.5, and 0.8), and RRs (0.5, 1.0, 5.0, 10.0, and 25.0). Subjects were randomly assigned with a risk based on the set of proportions-at-risk values. A disease occurred based on the baseline incidence among those not at risk. The incidence of those at risk was the product of the baseline incidence and the RRs. The 95% CIs of RRs were calculated according to Altman. Results The calculation of RR 95% CIs is not connected to the RR upper limits in equations. The RRs in the simulated populations at risk could reach the upper limits of RRs: multiplicative inverse of the baseline incidence. The upper limits to the derived RRs were around 1.25, 2, 3.3, 10, and 20, when the assumed baseline incidence rates were 0.8, 0.5, 0.3, 0.2, and 0.05, respectively. We demonstrated five scenarios in which the RR 95% CIs might exceed the upper limits. Conclusions Statistical significance does not imply the RR 95% CIs not exceeding the upper limits of RRs. When reporting RRs or ORs, the RR upper limits should be assessed. The rate ratio is also subject to a similar upper limit. In the literature, ORs tend to overestimate effect sizes. It is recommended to correct ORs that aim to approximate RRs assuming outcomes are rare. A reporting guide for relative measures, RRs, ORs, and rate ratios, is provided. Researchers are recommended to report whether the 95% CIs of relative measures, RRs, ORs, and rate ratios, overlap with the range of upper limits and discuss whether the relative measure estimates may exceed the upper limits.

Critical Hierarchical Appraisal and Reporting Tool for Composite Measures (CHAOS).

Background Composite measures are often used to represent certain concepts that cannot be measured with single variables and can be used as diagnoses, prognostic factors, or outcomes in clinical or health research. For example, frailty is a diagnosis confirmed based on the number of age-related symptoms and has been used to predict major health outcomes. However, undeclared assumptions and problems are prevalent among composite measures. Thus, we aim to propose a reporting guide and an appraisal tool for identifying these assumptions and problems. Methods We developed this reporting and assessment tool based on evidence and the consensus of experts pioneering research on index mining and syndrome mining. We designed a development framework for composite measures and then tested and revised it based on several composite measures commonly used in medical research, such as frailty, body mass index (BMI), mental illness diagnoses, and innovative indices mined for mortality prediction. We extracted review questions and reporting items from various issues identified by the development framework. This panel reviewed the identified issues, considered other aspects that might have been neglected in previous studies, and reached a consensus on the questions to be used by the reporting and assessment tool. Results We selected 19 questions in seven domains for reporting or critical assessment. Each domain contains review questions for authors and readers to critically evaluate the interpretability and validity of composite measures, which include candidate variable selection, variable inclusion and assumption declaration, data processing, weighting scheme, methods to aggregate information, composite measure interpretation and justification, and recommendations on the use. Conclusions For all seven domains, interpretability is central with respect to composite measures. Variable inclusion and assumptions are important clues to show the connection between composite measures and their theories. This tool can help researchers and readers understand the appropriateness of composite measures by exploring various issues. We recommend using this Critical Hierarchical Appraisal and repOrting tool for composite measureS (CHAOS) along with other critical appraisal tools to evaluate study design or risk of bias.

The sbiTRS Operon Contributes to Stenobactin-Mediated Iron Utilization in Stenotrophomonas maltophilia.

Iron is an essential micronutrient for various bacterial cellular processes. Fur is a global transcriptional regulator participating in iron homeostasis. Stenotrophomonas maltophilia is a ubiquitous environmental bacterium that has emerged as an opportunistic pathogen. To elucidate the novel regulatory mechanism behind iron homeostasis in S. maltophilia, wild-type KJ and KJΔFur, a fur mutant, were subjected to transcriptome assay. A five-gene cluster, sbiBA-sbiTRS, was significantly upregulated in KJΔFur. SbiAB is an ATP type efflux pump, SbiT is an inner membrane protein, and SbiSR is a two-component regulatory system (TCS). The sbiTRS operon organization was verified by reverse transcription-PCR (RT-PCR). Localization prediction and bacterial two-hybrid studies revealed that SbiT resided in the inner membrane and had an intramembrane interaction with SbiS. In iron-replete conditions, SbiT interacted with SbiS and maintained SbiSR TCS in a resting state. In response to iron depletion stress, SbiT no longer interacted with SbiS, leading to SbiSR TCS activation. The iron source utilization assay demonstrated the contribution of SbiSR TCS to stenobactin-mediated ferric iron utilization but notto the utilization of hemin and ferric citrate. Furthermore, SmeDEF and SbiAB pumps, known stenobactin secretion outlets, were members of the SbiSR regulon. Collectively, in an iron-depleted condition, SbiSR activation is regulated by Fur at the transcriptional level and by SbiT at the posttranslational level. Activated SbiSR contributes to stenobactin-mediated ferric iron utilization by upregulating the smeDEF and sbiAB operons. SbiSR is the first TCS found to be involved in iron homeostasis in S. maltophilia. IMPORTANCE Therapeutic options for Stenotrophomonas maltophilia infections are limited because S. maltophilia is intrinsically resistant to several antibiotics. Iron is an essential element for viability, but iron overload is a lethal threat to bacteria. Therefore, disruption of iron homeostasis can be an alternative strategy to cope with S. maltophilia infection. The intricate regulatory networks involved in iron hemostasis have been reported in various pathogens; however, little is known about S. maltophilia. Herein, a novel sbiTRS operon, a member of Fur regulon, was characterized. SbiT, an inner membrane protein, negatively modulated the SbiSR two-component regulatory system by intramembrane protein-protein interaction with SbiS. In response to iron-depleted stress, SbiSR was activated via the regulation of Fur and SbiT. Activated SbiSR upregulated smeDEF and sbiAB, which contributed to stenobactin-mediated ferric iron utilization. A novel fur-sbiT-sbiSR-smeDEF/sbiAB regulatory circuit in S. maltophilia was revealed.

Frailty does not cause all frail symptoms: United States Health and Retirement Study.

BACKGROUND: Frailty is associated with major health outcomes. However, the relationships between frailty and frailty symptoms haven't been well studied. This study aims to show the associations between frailty and frailty symptoms. METHODS: The Health and Retirement Study (HRS) is an ongoing longitudinal biannual survey in the United States. Three of the most used frailty diagnoses, defined by the Functional Domains Model, the Burden Model, and the Biologic Syndrome Model, were reproduced according to previous studies. The associations between frailty statuses and input symptoms were assessed using odds ratios and correlation coefficients. RESULTS: The sample sizes, mean ages, and frailty prevalence matched those reported in previous studies. Frailty statuses were weakly correlated with each other (coefficients = 0.19 to 0.38, p < 0.001 for all). There were 49 input symptoms identified by these three models. Frailty statuses defined by the three models were not significantly correlated with one or two symptoms defined by the same models (p > 0.05 for all). One to six symptoms defined by the other two models were not significantly correlated with each of the three frailty statuses (p > 0.05 for all). Frailty statuses were significantly correlated with their own bias variables (p < 0.05 for all). CONCLUSION: Frailty diagnoses lack significant correlations with some of their own frailty symptoms and some of the frailty symptoms defined by the other two models. This finding raises questions like whether the frailty symptoms lacking significant correlations with frailty statuses could be included to diagnose frailty and whether frailty exists and causes frailty symptoms.

σP-NagA-L1/L2 Regulatory Circuit Involved in ΔompA299-356-Mediated Increase in ß-Lactam Susceptibility in Stenotrophomonas maltophilia.

OmpA, the most abundant porin in Stenotrophomonas maltophilia KJ, exists as a two-domain structure with an N-terminal domain of ß-barrel structure embedded in the outer membrane and a C-terminal domain collocated in the periplasm. KJΔOmpA299-356, an ompA mutant of S. maltophilia KJ with a truncated OmpA devoid of 299 to 356 amino acids (aa), was able to stably embed in the outer membrane. KJΔOmpA299-356 was more susceptible to ß-lactams than wild-type KJ. We aimed to elucidate the mechanism underlying the ΔompA299-356-mediated increase in ß-lactam susceptibility (abbreviated as "ΔOmpA299-356 phenotype"). KJΔOmpA299-356 displayed a lower ceftazidime (CAZ)-induced ß-lactamase activity than KJ. Furthermore, KJ2, a L1/L2 ß-lactamases-null mutant, and KJ2ΔOmpA299-356, a KJ2 mutant with truncated OmpA devoid of299 to 356 aa, had comparable ß-lactam susceptibility. Both lines of evidence indicate that decreased ß-lactamase activity contributes to the ΔOmpA299-356 phenotype. We analyzed the transcriptome results of KJ and KJΔOmpA299-356, focusing on PG homeostasis-associated genes. Among the 36 genes analyzed, the nagA gene was upregulated 4.65-fold in KJΔOmpA299-356. Deletion of the nagA gene from the chromosome of KJΔOmpA299-356 restored ß-lactam susceptibility and CAZ-induced ß-lactamase activity to wild-type levels, verifying that nagA-upregulation in KJΔOmpA299-356 contributes to the ΔOmpA299-356 phenotype. Furthermore, transcriptome analysis revealed that rpoE (Smlt3555) and rpoP (Smlt3514) were significantly upregulated in KJΔOmpA299-356. The deletion mutant construction, ß-lactam susceptibility, and ß-lactamase activity analysis demonstrated that σP, but not σE, was involved in the ΔOmpA299-356 phenotype. A real-time quantitative (qRT-PCR) assay confirmed that nagA is a member of the σP regulon. The involvement of the σP-NagA-L1/L2 regulatory circuit in the ΔOmpA299-356 phenotype was manifested. IMPORTANCE Porins of Gram-negative bacteria generally act as channels that allow the entry or extrusion of molecules. Moreover, the structural role of porins in stabilizing the outer membrane by interacting with peptidoglycan (PG) and the outer membrane has been proposed. The linkage between porin deficiency and antibiotic resistance increase has been reported widely, with a rationale for blocking antibiotic influx. In this study, a link between porin defects and ß-lactam susceptibility increase was demonstrated. The underlying mechanism revealed that a novel σP-NagA-L1/L2 regulatory circuit is triggered due to the loss of the OmpA-PG interaction. This study extends the understanding on the porin defect and antibiotic susceptibility. Porin defects may cause opposite impacts on antibiotic susceptibility, which is dependent on the involvement of the defect. Blocking the porin channel role can increase antibiotic resistance; in contrast, the loss of porin structure role may increase antibiotic susceptibility.

Diagnostic accuracy of symptoms for an underlying disease: a simulation study.

Symptoms have been used to diagnose conditions such as frailty and mental illnesses. However, the diagnostic accuracy of the numbers of symptoms has not been well studied. This study aims to use equations and simulations to demonstrate how the factors that determine symptom incidence influence symptoms' diagnostic accuracy for disease diagnosis. Assuming a disease causing symptoms and correlated with the other disease in 10,000 simulated subjects, 40 symptoms occurred based on 3 epidemiological measures: proportions diseased, baseline symptom incidence (among those not diseased), and risk ratios. Symptoms occurred with similar correlation coefficients. The sensitivities and specificities of single symptoms for disease diagnosis were exhibited as equations using the three epidemiological measures and approximated using linear regression in simulated populations. The areas under curves (AUCs) of the receiver operating characteristic (ROC) curves was the measure to determine the diagnostic accuracy of multiple symptoms, derived by using 2 to 40 symptoms for disease diagnosis. With respect to each AUC, the best set of sensitivity and specificity, whose difference with 1 in the absolute value was maximal, was chosen. The results showed sensitivities and specificities of single symptoms for disease diagnosis were fully explained with the three epidemiological measures in simulated subjects. The AUCs increased or decreased with more symptoms used for disease diagnosis, when the risk ratios were greater or less than 1, respectively. Based on the AUCs, with risk ratios were similar to 1, symptoms did not provide diagnostic values. When risk ratios were greater or less than 1, maximal or minimal AUCs usually could be reached with less than 30 symptoms. The maximal AUCs and their best sets of sensitivities and specificities could be well approximated with the three epidemiological and interaction terms, adjusted R-squared ≥ 0.69. However, the observed overall symptom correlations, overall symptom incidence, and numbers of symptoms explained a small fraction of the AUC variances, adjusted R-squared ≤ 0.03. In conclusion, the sensitivities and specificities of single symptoms for disease diagnosis can be explained fully by the at-risk incidence and the 1 minus baseline incidence, respectively. The epidemiological measures and baseline symptom correlations can explain large fractions of the variances of the maximal AUCs and the best sets of sensitivities and specificities. These findings are important for researchers who want to assess the diagnostic accuracy of composite diagnostic criteria.

Draft Genome Sequence of Stenotrophomonas maltophilia KJ, a Clinical Isolate from Taiwan.

We report the draft genome sequence of Stenotrophomonas maltophilia strain KJ, which was isolated from a sputum sample from a patient with a respiratory tract infection. Multilocus sequence typing analysis suggested that strain KJ belongs to a novel S. maltophilia sequence type.

Roles of SmeYZ, SbiAB, and SmeDEF Efflux Systems in Iron Homeostasis of Stenotrophomonas maltophilia.

Stenotrophomonas maltophilia, a nonfermenting Gram-negative rod, is frequently isolated from the environment and is emerging as a multidrug-resistant global opportunistic pathogen. S. maltophilia harbors eight RND-type efflux pumps that contribute to multidrug resistance and physiological functions. Among the eight efflux pumps, SmeYZ pump is constitutively highly expressed. In our previous study, we demonstrated that loss-of-function of the SmeYZ pump results in pleiotropic phenotypes, including abolished swimming motility, decreased secreted protease activity, and compromised tolerance to oxidative stress and antibiotics. In this study, we attempted to elucidate the underlying mechanisms responsible for ΔsmeYZ-mediated pleiotropic phenotypes. RNA-seq transcriptome analysis and subsequent confirmation with qRT-PCR revealed that smeYZ mutant experienced an iron starvation response because the genes involved in the synthesis and uptake of stenobactin, the sole siderophore of S. maltophilia, were significantly upregulated. We further verified that smeYZ mutant had low intracellular iron levels via inductively coupled plasma mass spectrometry (ICP-MS). Also, KJΔYZ was more sensitive to 2,2'-dipyridyl (DIP), a ferrous iron chelator, in comparison with the wild type. The contribution of SmeYZ, SmeDEF, and SbiAB pumps to stenobactin secretion was suggested by qRT-PCR and further verified by Chrome Azurol S (CAS) activity, iron source utilization, and cell viability assays. We also demonstrated that loss-of-function of SmeYZ led to the compensatory upregulation of SbiAB and SmeDEF pumps for stenobactin secretion. The overexpression of the SbiAB pump resulted in a reduction in intracellular iron levels, which may be the key factor responsible for the ΔsmeYZ-mediated pleiotropic phenotypes, except for antibiotic extrusion. IMPORTANCE Efflux pumps display high efficiency of drug extrusion, which underlies their roles in multidrug resistance. In addition, efflux pumps have physiological functions, and their expression is tightly regulated by various environmental and physiological signals. Functional redundancy of efflux pumps is commonly observed, and mutual regulation occurs among these functionally redundant pumps in a bacterium. Stenotrophomonas maltophilia is an opportunistic pathogen that shows intrinsic multi-drug resistance. In this study, we demonstrated that SmeYZ, SbiAB, and SmeDEF efflux pumps of S. maltophilia display functional redundancy in siderophore secretion. Inactivation of smeYZ led to the upregulation of smeDEF and sbiAB. Unexpectedly, sbiAB overexpression resulted in the reduction of intracellular iron levels, which led to pleiotropic defects in smeYZ mutant. This study demonstrates a previously unidentified connection between efflux pumps, siderophore secretion, and intracellular iron levels in S. maltophilia.

Why Mental Illness Diagnoses Are Wrong: A Pilot Study on the Perspectives of the Public.

Background: Mental illness diagnostic criteria are made based on assumptions. This pilot study aims to assess the public's perspectives on mental illness diagnoses and these assumptions. Methods: An anonymous survey with 30 questions was made available online in 2021. Participants were recruited via social media, and no personal information was collected. Ten questions focused on participants' perceptions regarding mental illness diagnoses, and 20 questions related to the assumptions of mental illness diagnoses. The participants' perspectives on these assumptions held by professionals were assessed. Results: Among 14 survey participants, 4 correctly answered the relationships of 6 symptom pairs (28.57%). Two participants could not correctly conduct the calculations involved in mood disorder diagnoses (14.29%). Eleven (78.57%) correctly indicated that 2 or more sets of criteria were available for single diagnoses of mental illnesses. Only 1 (7.14%) correctly answered that the associations between symptoms and diagnoses were supported by including symptoms in the diagnostic criteria of the diagnoses. Nine (64.29%) correctly answered that the diagnosis variances were not fully explained by their symptoms. The confidence of participants in the major depressive disorder diagnosis and the willingness to take medications for this diagnosis were the same (mean = 5.50, standard deviation [SD] = 2.31). However, the confidence of participants in the symptom-based diagnosis of non-solid brain tumor was significantly lower (mean = 1.62, SD = 2.33, p < 0.001). Conclusion: Our study found that mental illness diagnoses are wrong from the perspectives of the public because our participants did not agree with all the assumptions professionals make about mental illness diagnoses. Only a minority of our participants obtained correct answers to the calculations involved in mental illness diagnoses. In the literature, neither patients nor the public have been engaged in formulating the diagnostic criteria of mental illnesses.

Evaluation of math anxiety and its remediation through a digital training program in mathematics for first and second graders.

INTRODUCTION: Math anxiety severely impacts individuals' learning and future success. However, limited is understood about the profile in East Asian cultures where students genuinely show high-level math anxiety, despite that they outperform their Western counterparts. Here, we investigate the relation between math anxiety and math achievement in children as young as first and second graders in Taiwan. Further, we evaluate whether intensive exposure to digital game-based learning in mathematics could ameliorate math anxiety. METHODS: The study first evaluated a group of 159 first and second graders' math anxiety and its correlation with math performance. Subsequently, a quasi-experimental design was adopted: 77 of the children continued and participated in multi-component digital game training targeting enumeration, speeded calculation, and working memory. Post-assessment was administered afterward for further evaluation of training-associated effects. RESULTS: Results confirmed that math anxiety was negatively associated with school math achievement, which assessed numerical knowledge and arithmetic calculation. Furthermore, children's math anxiety was remarkably reduced via digital training in mathematics after 6-week intensive remediation. Crucially, this math anxiety relief was more prominent in those with high-level math anxiety. Although the children who underwent the training showed training-induced math achievement and working memory enhancement, this cognitive improvement appeared to be independent of the math anxiety relief. CONCLUSION: Our findings demonstrate that students can show highly negative emotions and perceptions toward learning even in high-achieving countries. Auspiciously, the feeling of distress toward learning has the feasibility to be relieved from short-term intensive training. Our study suggests a new approach of early treatments to emotional disturbance that can lead to permanent consequences in individuals.

Interpretable Trials: Is Interpretability a Reason Why Clinical Trials Fail?

Background: There are clinical trials using composite measures, indices, or scales as proxy for independent variables or outcomes. Interpretability of derived measures may not be satisfying. Adopting indices of poor interpretability in clinical trials may lead to trial failure. This study aims to understand the impact of using indices of different interpretability in clinical trials. Methods: The interpretability of indices was categorized as: fair-to-poor, good, and unknown. In the literature, frailty indices were considered fair to poor interpretability. Body mass index (BMI) was highly interpretable. The other indices were of unknown interpretability. The trials were searched at clinicaltrials.gov on October 2, 2018. The use of indices as conditions/diseases or other terms was searched. The trials were grouped as completed, terminated, active, and other status. We tabulated the frequencies of frailty, BMI, and other indices. Results: There were 263,928 clinical trials found and 155,606 were completed or terminated. Among 2,115 trials adopting indices or composite measures as condition or disease, 244 adopted frailty and 487 used BMI without frailty indices. Significantly higher proportions of trials of unknown status used indices as conditions/diseases or other terms, compared to completed and terminated trials. The proportions of active trials using frailty indices were significantly higher than those of completed or terminated trials. Discussion: Clinical trial databases can be used to understand why trials may fail. Based on the findings, we suspect that using indices of poor interpretability may be associated with trial failure. Interpretability has not been conceived as an essential criterion for outcomes or proxy measures in trials. We will continue verifying the findings in other databases or data sources and apply this research method to improve clinical trial design. To prevent patients from experiencing trials likely to fail, we suggest further examining the interpretability of the indices in trials.

Simulation study to demonstrate biases created by diagnostic criteria of mental illnesses: major depressive episodes, dysthymia, and manic episodes.

OBJECTIVES: Composite diagnostic criteria alone are likely to create and introduce biases into diagnoses that subsequently have poor relationships with input symptoms. This study aims to understand the relationships between the diagnoses and the input symptoms, as well as the magnitudes of biases created by diagnostic criteria and introduced into the diagnoses of mental illnesses with large disease burdens (major depressive episodes, dysthymic disorder, and manic episodes). SETTINGS: General psychiatric care. PARTICIPANTS: Without real-world data available to the public, 100 000 subjects were simulated and the input symptoms were assigned based on the assumed prevalence rates (0.05, 0.1, 0.3, 0.5 and 0.7) and correlations between symptoms (0, 0.1, 0.4, 0.7 and 0.9). The input symptoms were extracted from the diagnostic criteria. The diagnostic criteria were transformed into mathematical equations to demonstrate the sources of biases and convert the input symptoms into diagnoses. PRIMARY AND SECONDARY OUTCOMES: The relationships between the input symptoms and diagnoses were interpreted using forward stepwise linear regressions. Biases due to data censoring or categorisation introduced into the intermediate variables, and the three diagnoses were measured. RESULTS: The prevalence rates of the diagnoses were lower than those of the input symptoms and proportional to the assumed prevalence rates and the correlations between the input symptoms. Certain input or bias variables consistently explained the diagnoses better than the others. Except for 0 correlations and 0.7 prevalence rates of the input symptoms for the diagnosis of dysthymic disorder, the input symptoms could not fully explain the diagnoses. CONCLUSIONS: There are biases created due to composite diagnostic criteria and introduced into the diagnoses. The design of the diagnostic criteria determines the prevalence of the diagnoses and the relationships between the input symptoms, the diagnoses, and the biases. The importance of the input symptoms has been distorted largely by the diagnostic criteria.

Opportunities and Challenges From Leading Trends in a Biomonitoring Project: Canadian Health Measures Survey 2007-2017.

Background: Biomonitoring can be conducted by assessing the levels of chemicals in human bodies and their surroundings, for example, as was done in the Canadian Health Measures Survey (CHMS). This study aims to report the leading increasing or decreasing biomarker trends and determine their significance. Methods: We implemented a trend analysis for all variables from CHMS biomonitoring data cycles 1-5 conducted between 2007 and 2017. The associations between time and obesity were determined with linear regressions using the CHMS cycles and body mass index (BMI) as predictors. Results: There were 997 unique biomarkers identified and 86 biomarkers with significant trends across cycles. Nine of the 10 leading biomarkers with the largest decreases were environmental chemicals. The levels of 1,2,3-trimethyl benzene, dodecane, palmitoleic acid, and o-xylene decreased by more than 60%. All of the 10 chemicals with the largest increases were environmental chemicals, and the levels of 1,2,4-trimethylbenzene, nonanal, and 4-methyl-2-pentanone increased by more than 200%. None of the 20 biomarkers with the largest increases or decreases between cycles were associated with BMI. Conclusions: The CHMS provides the opportunity for researchers to determine associations between biomarkers and time or BMI. However, the unknown causes of trends with large magnitudes of increase or decrease and their unclear impact on Canadians' health present challenges. We recommend that the CHMS plan future cycles on leading trends and measure chemicals with both human and environmental samples.

Using syndrome mining with the Health and Retirement Study to identify the deadliest and least deadly frailty syndromes.

Syndromes are defined with signs or symptoms that occur together and represent conditions. We use a data-driven approach to identify the deadliest and most death-averse frailty syndromes based on frailty symptoms. A list of 72 frailty symptoms was retrieved based on three frailty indices. We used data from the Health and Retirement Study (HRS), a longitudinal study following Americans aged 50 years and over. Principal component (PC)-based syndromes were derived based on a principal component analysis of the symptoms. Equal-weight 4-item syndromes were the sum of any four symptoms. Discrete-time survival analysis was conducted to compare the predictive power of derived syndromes on mortality. Deadly syndromes were those that significantly predicted mortality with positive regression coefficients and death-averse ones with negative coefficients. There were 2,797 of 5,041 PC-based and 964,774 of 971,635 equal-weight 4-item syndromes significantly associated with mortality. The input symptoms with the largest regression coefficients could be summed with three other input variables with small regression coefficients to constitute the leading deadliest and the most death-averse 4-item equal-weight syndromes. In addition to chance alone, input symptoms' variances and the regression coefficients or p values regarding mortality prediction are associated with the identification of significant syndromes.

Protection from hydrogen peroxide stress relies mainly on AhpCF and KatA2 in Stenotrophomonas maltophilia.

BACKGROUND: Aerobically-grown bacteria can be challenged by hydrogen peroxide stress from endogenous aerobic metabolism and exogenously generated reactive oxygen species. Catalase (Kat), alkyl hydroperoxidase (Ahp), and glutathione peroxidase (Gpx) systems are major adaptive responses to H2O2 stress in bacteria. Stenotrophomonas maltophilia is a ubiquitous Gram-negative bacterium equipped with four Kats (KatA1, KatA2, KatMn, and KatE), one Ahp (AhpCF), and three Gpxs (Gpx1, Gpx2, and Gpx3). Here, we systematically investigated how the eight H2O2 scavenging genes differentially contribute to the low-micromolar levels of H2O2 generated from aerobic metabolism and high-millimolar levels of H2O2 from exogenous sources. METHODS: Gene expression was assessed and quantified by reverse transcription-PCR (RT-PCR) and real time quantitative PCR (qRT-PCR), respectively. The contribution of these enzymes to H2O2 stress was assessed using mutant construction and functional investigation. RESULTS: Of the eight genes, katA2, ahpCF, and gpx3 were intrinsically expressed in response to low-micromolar levels of H2O2 from aerobic metabolism, and the expression of katA2 and ahpCF was regulated by OxyR. AhpCF and KatA2 were responsible for alleviating aerobic growth-mediated low concentration H2O2 stress and AhpCF played a critical role for stationary-phase cells. KatA2 was upregulated to compensate for AhpCF in the case of ahpCF inactivation. After exposure to millimolar levels of H2O2, katA2 and ahpCF were upregulated in an OxyR-dependent manner. KatA2 was the critical enzyme for dealing with high concentration H2O2. Loss-of-function of KatA2 increased bacterial susceptibility to high concentration H2O2. CONCLUSIONS: AhpCF and KatA2 are key enzymes protecting S. maltophilia from hydrogen peroxide stress.

Composite diagnostic criteria are problematic for linking potentially distinct populations: the case of frailty.

Composite diagnostic criteria are common in frailty research. We worry distinct populations may be linked to each other due to complicated criteria. We aim to investigate whether distinct populations might be considered similar based on frailty diagnostic criteria. The Functional Domains Model for frailty diagnosis included four domains: physical, nutritive, cognitive and sensory functioning. Health and Retirement Study participants with two or more deficiencies in the domains were diagnosed frail. The survival distributions were analyzed using discrete-time survival analysis. The distributions of the demographic characteristics and survival across the groups diagnosed with frailty were significantly different (p < 0.05). A deficiency in cognitive functioning was associated with the worst survival pattern compared with a deficiency in the other domains (adjusted p < 0.05). The associations of the domains with mortality were cumulative without interactions. Cognitive functioning had the largest effect size for mortality prediction (Odds ratios, OR = 2.37), larger than that of frailty status (OR = 1.92). The frailty diagnostic criteria may take distinct populations as equal and potentially assign irrelevant interventions to individuals without corresponding conditions. We think it necessary to review the adequacy of composite diagnostic criteria in frailty diagnosis.

Overexpression of SmeGH contributes to the acquired MDR of Stenotrophomonas maltophilia.

BACKGROUND: Stenotrophomonas maltophilia displays high-level resistance to various antibiotics. Fluoroquinolone is among the few treatment options for S. maltophilia infection. Overexpression of SmeDEF, SmeVWX and SmQnr are the main mechanisms responsible for fluoroquinolone resistance in S. maltophilia. OBJECTIVES: To reveal the unidentified fluoroquinolone resistance mechanisms in S. maltophilia. METHODS: Fluoroquinolone-resistant spontaneous mutants were selected by spreading KJΔDEFΔ5, a SmeDEF- and SmeVWX-null double mutant, on ciprofloxacin- or levofloxacin-containing medium. Antibiotic susceptibility was assessed by the agar dilution method. Outer membrane protein profiles of fluoroquinolone-resistant mutants were assayed by SDS-PAGE and significant protein was characterized by LC-MS/MS. The expression of tolCsm, smeH, smeK, smeN, smeP, smeZ and smQnr was investigated by real-time quantitative PCR. The contribution of SmeGH overexpression to antibiotic resistance was verified by ΔsmeH mutant construction and smeGH complementation assay. RESULTS: Most fluoroquinolone-resistant mutants displayed MDR. The TolCsm protein and smeH transcript were concomitantly overexpressed in some MDR mutants. smeH deletion increased the susceptibility of the MDR mutants to fluoroquinolone, macrolide, chloramphenicol and tetracycline, and the resistance compromise was partially reversed by complementation with a plasmid containing smeGH. SmeGH overexpression was found in some fluoroquinolone-resistant clinical S. maltophilia isolates whose SmeDEF, SmeVWX and SmQnr proteins were not or were lowly expressed. CONCLUSIONS: Overexpression of SmeGH contributes to the acquired resistance of S. maltophilia to fluoroquinolone, macrolide, chloramphenicol and tetracycline.

Substantial Contribution of SmeDEF, SmeVWX, SmQnr, and Heat Shock Response to Fluoroquinolone Resistance in Clinical Isolates of Stenotrophomonas maltophilia.

Stenotrophomonas maltophilia is an emerging multi-drug resistant opportunistic pathogen. Although fluoroquinolones (FQ) are still clinically valuable for the treatment of S. maltophilia infection, an increasing prevalence in FQ resistance has been reported. Overexpression of SmeDEF, SmeVWX, and SmQnr, and de-repressed expression of heat shock response are reported mechanisms responsible for FQ resistance in S. maltophilia; nevertheless, some of these mechanisms are identified from laboratory-constructed mutants, and it remains unclear whether they occur in clinical setting. In this study, we aimed to assess whether these mechanisms contribute substantially to FQ resistance in clinical isolates. Eighteen ciprofloxacin- and levofloxacin-resistant isolates were selected from 125 clinical isolates of S. maltophilia. The expression of smeE, smeW, and Smqnr genes of these isolates was investigated by RT-qPCR. The de-repressed heat shock response was assessed by rpoE expression at 37°C and bacterial viability at 40°C. The contribution of SmeDEF, SmeVWX, and SmQnr, and heat shock response to FQ resistance was evaluated by mutants construction and susceptibility testing. The results demonstrated that simply assessing the overexpression of SmeDEF, SmeVWX, and SmQnr by RT-qPCR may overestimate their contribution to FQ resistance. Simultaneous overexpression of SmeDEF and SmeVWX did not increase the resistance level to their common substrates, but extended the resistance spectrum. Moreover, the de-repressed expression of heat shock response was not observed to contribute to FQ resistance in the clinical isolates of S. maltophilia.