Existing high-throughput methods to identify RNA-binding proteins (RBPs) involving capture of polyadenylated RNAs can not recover proteins that interact with non-adenylated RNAs, including lncRNA, pre-mRNA and bacterial RNAs. We present orthogonal organic phase separation (OOPS) which does not require molecular tagging or capture of polyadenylated RNA. We verify OOPS in HEK293, U2OS and MCF10A human cell lines, finding 96% of proteins recovered are bound to RNA. We demonstrate that all long RNAs can be crosslinked to proteins and recover 1838 RBPs, including 926 putative novel RBPs. Importantly, OOPS is approximately 100-fold more efficient than current techniques, enabling analysis of dynamic RNA-protein interactions. We identified 749 proteins with altered RNA binding following release from nocodazole arrest. Finally, OOPS allowed the characterisation of the first RNA-interactome for a bacterium, Escherichia coli. OOPS is an easy to use and flexible technique, compatible with downstream proteomics and RNA sequencing and applicable to any organism.

The vast personal and economic burden of mood disorders is largely caused by their under- and misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. Here, we aimed to develop a diagnostic algorithm, based on an online questionnaire and blood biomarker data, to reduce the misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD). Individuals with depressive symptoms (Patient Health Questionnaire-9 score ≥5) aged 18–45 years were recruited online. After completing a purpose-built online mental health questionnaire, eligible participants provided dried blood spot samples for biomarker analysis and underwent the World Health Organization World Mental Health Composite International Diagnostic Interview via telephone, to establish their mental health diagnosis. Extreme Gradient Boosting and nested cross-validation were used to train and validate diagnostic models differentiating BD from MDD in participants who self-reported a current MDD diagnosis. Mean test area under the receiver operating characteristic curve (AUROC) for separating participants with BD diagnosed as MDD (N = 126) from those with correct MDD diagnosis (N = 187) was 0.92 (95% CI: 0.86–0.97). Core predictors included elevated mood, grandiosity, talkativeness, recklessness and risky behaviour. Additional validation in participants with no previous mood disorder diagnosis showed AUROCs of 0.89 (0.86–0.91) and 0.90 (0.87–0.91) for separating newly diagnosed BD (N = 98) from MDD (N = 112) and subclinical low mood (N = 120), respectively. Validation in participants with a previous diagnosis of BD (N = 45) demonstrated sensitivity of 0.86 (0.57–0.96). The diagnostic algorithm accurately identified patients with BD in various clinical scenarios, and could help expedite accurate clinical diagnosis and treatment of BD.

Background Web-based assessments of mental health concerns hold great potential for earlier, more cost-effective, and more accurate diagnoses of psychiatric conditions than that achieved with traditional interview-based methods. Objective The aim of this study was to assess the impact of a comprehensive web-based mental health assessment on the mental health and well-being of over 2000 individuals presenting with symptoms of depression. Methods Individuals presenting with depressive symptoms completed a web-based assessment that screened for mood and other psychiatric conditions. After completing the assessment, the study participants received a report containing their assessment results along with personalized psychoeducation. After 6 and 12 months, participants were asked to rate the usefulness of the web-based assessment on different mental health–related outcomes and to self-report on their recent help-seeking behavior, diagnoses, medication, and lifestyle changes. In addition, general mental well-being was assessed at baseline and both follow-ups using the Warwick-Edinburgh Mental Well-being Scale (WEMWBS). Results Data from all participants who completed either the 6-month or the 12-month follow-up (N=2064) were analyzed. The majority of study participants rated the study as useful for their subjective mental well-being. This included talking more openly (1314/1939, 67.77%) and understanding one’s mental health problems better (1083/1939, 55.85%). Although most participants (1477/1939, 76.17%) found their assessment results useful, only a small proportion (302/2064, 14.63%) subsequently discussed them with a mental health professional, leading to only a small number of study participants receiving a new diagnosis (110/2064, 5.33%). Among those who were reviewed, new mood disorder diagnoses were predicted by the digital algorithm with high sensitivity (above 70%), and nearly half of the participants with new diagnoses also had a corresponding change in medication. Furthermore, participants’ subjective well-being significantly improved over 12 months (baseline WEMWBS score: mean 35.24, SD 8.11; 12-month WEMWBS score: mean 41.19, SD 10.59). Significant positive predictors of follow-up subjective well-being included talking more openly, exercising more, and having been reviewed by a psychiatrist. Conclusions Our results suggest that completing a web-based mental health assessment and receiving personalized psychoeducation are associated with subjective mental health improvements, facilitated by increased self-awareness and subsequent use of self-help interventions. Integrating web-based mental health assessments within primary and/or secondary care services could benefit patients further and expedite earlier diagnosis and effective treatment. International Registered Report Identifier (IRRID) RR2-10.2196/18453

27Current methods for the identification of RNA-protein interactions require a quantity and 28 quality of sample that hinders their application, especially for dynamic biological 29 systems or when sample material is limiting. Here, we present a new approach to enrich 30 RNA-Binding Proteins (RBPs): Orthogonal Organic Phase Separation (OOPS), which is 31 compatible with downstream proteomics and RNA sequencing. OOPS enables recovery 32 of RBPs and free protein, or protein-bound RNA and free RNA, from a single sample in 33 an unbiased manner. By applying OOPS to human cell lines, we extract the majority of 34 known RBPs, and importantly identify additional novel RBPs, including those from 35 previously under-represented cellular compartments. The high yield and unbiased 36 nature of OOPS facilitates its application in both dynamic and inaccessible systems. 37 Thus, we have identified changes in RNA-protein interactions in mammalian cells 38 following nocodazole cell-cycle arrest, and defined the first bacterial RNA-interactome. 39 Overall, OOPS provides an easy-to-use and flexible technique that opens new 40 opportunities to characterize RNA-protein interactions and explore their dynamic 41 behaviour. 42 43 44 59 conditions 13 . Moreover, the theoretical dependence on the presence of RNA polyA tails, 60 makes oligo(dT)-based capture methods incompatible for organisms with little or no 61 polyadenylation, such as prokaryotes, or for non-polyadenylated RNAs; thus introducing 62 bias in the RBPs identified. There have been recent attempts to address the oligo(dT) 63 limitations, but these have involved incorporation of modified nucleotides, which by itself 64 restricts its applicability and introduces a bias in transcription-dependent nucleoside-65 incorporation 14-16 . 66 67 2 To address these limitations, we have developed a method based on Acidic 68 Guanidinium Thiocyanate-Phenol-Chloroform (AGPC) phase partition, called 69 Orthogonal Organic Phase Separation (OOPS). AGPC purification permits the recovery 70 of RNA species in an unbiased manner 17,18 . In standard conditions, when lysing cells in 71 AGPC, two distinct phases are formed: RNA migrates to the upper aqueous phase and 72 proteins occupy the lower organic phase. Here, we utilise UV crosslinking at 254 nm to 73 generate RNA-protein adducts that combine the physicochemical properties of both 74 molecules and thus migrate to the aqueous-organic interface 19 . Isolation of the interface 75 allows specific recovery of either RBPs or PBRs by digesting the reciprocal component 76 of the adduct. 77 78 Here, we demonstrate the specificity and versatility of OOPS. Separation of free and 79 protein-bound RNA provides a way to quantify the proportion of RNA crosslinked to 80 protein, enabling precise optimisation of UV dosage. Furthermore, we show that OOPS 81 recovers all crosslinked-RNA (CL-RNA) and thus all crosslinked RBPs. To demonstrate 82 the versatility of OOPS, we analyse RNA-binding changes through cell-cycle 83 progression following noc...

In the version of this article initially published, we listed 13 companies that were developing phage therapies a decade ago and stated that only a few are still active today. Missing from the active list was Phico Therapeutics of Bourn, UK. In addition, a location (Canada) has been added for PhageTech, and "Last May" has been changed to "In May" at the beginning of the article. The errors have been corrected in the HTML and PDF versions of the article.

Background Diagnosing major depressive disorder (MDD) is challenging, with diagnostic manuals failing to capture the wide range of clinical symptoms that are endorsed by individuals with this condition. Objective This study aims to provide evidence for an extended definition of MDD symptomatology. Methods Symptom data were collected via a digital assessment developed for a delta study. Random forest classification with nested cross-validation was used to distinguish between individuals with MDD and those with subthreshold symptomatology of the disorder using disorder-specific symptoms and transdiagnostic symptoms. The diagnostic performance of the Patient Health Questionnaire–9 was also examined. Results A depression-specific model demonstrated good predictive performance when distinguishing between individuals with MDD (n=64) and those with subthreshold depression (n=140) (area under the receiver operating characteristic curve=0.89; sensitivity=82.4%; specificity=81.3%; accuracy=81.6%). The inclusion of transdiagnostic symptoms of psychopathology, including symptoms of depression, generalized anxiety disorder, insomnia, emotional instability, and panic disorder, significantly improved the model performance (area under the receiver operating characteristic curve=0.95; sensitivity=86.5%; specificity=90.8%; accuracy=89.5%). The Patient Health Questionnaire–9 was excellent at identifying MDD but overdiagnosed the condition (sensitivity=92.2%; specificity=54.3%; accuracy=66.2%). Conclusions Our findings are in line with the notion that current diagnostic practices may present an overly narrow conception of mental health. Furthermore, our study provides proof-of-concept support for the clinical utility of a digital assessment to inform clinical decision-making in the evaluation of MDD.

BACKGROUND Diagnosing major depressive disorder (MDD) is challenging, with diagnostic manuals failing to capture the wide range of clinical symptoms that are endorsed by individuals with the condition. OBJECTIVE The aim of this study was to provide evidence for an extended definition of MDD symptomatology. METHODS Symptom data were collected via a digital assessment that was developed for the Delta Study [1]. Random forest classification with nested cross-validation was used to distinguish between individuals with MDD and those with subthreshold symptomatology of the disorder using i) disorder-specific symptoms and ii) transdiagnostic symptoms. The diagnostic performance of the Patient Health Questionnaire-9 (PHQ-9) was also examined. RESULTS A depression-specific model demonstrated good predictive performance when distinguishing between individuals with MDD (n = 64) and those with subthreshold depression (n = 140) (AUC = .89; sensitivity = 82.4%; specificity = 81.3%; accuracy = 81.6%). The inclusion of transdiagnostic symptoms of psychopathology, including symptoms of depression, generalized anxiety disorder, insomnia, emotional instability, and panic disorder, improved the model performance (AUC = .95; sensitivity = 86.5%; specificity = 90.8%; accuracy = 89.5%). The PHQ-9 was excellent at identifying MDD but over diagnosed the condition (sensitivity = 92.2%; specificity = 54.3%; accuracy = 66.2%). CONCLUSIONS Our findings are in line with the notion that current diagnostic practices may present an overly narrow conception of mental health. Further, our study provides proof-of-concept support for the clinical utility of a digital assessment to inform clinical decision-making in the evaluation of MDD.

BACKGROUND Online assessments of mental health concerns hold great potential for earlier, more cost-effective and more accurate diagnosis of psychiatric conditions compared to traditional interview-based methods. OBJECTIVE To assess the impact of a comprehensive online mental health assessment on mental health and wellbeing in over 2000 individuals presenting with symptoms of depression. METHODS Participants in the Delta Study presenting with depressive symptoms at baseline completed an online assessment which screened for mood and other psychiatric conditions. After completing the assessment, participants received a report containing their assessment results and personalised psychoeducation. After 6 and 12 months, participants were asked to rate the usefulness of the online assessment on different mental health-related outcomes, as well as to self-report on their recent help-seeking behaviour, diagnosis, medication and lifestyle changes. Additionally, general mental wellbeing was assessed at baseline and both follow-ups using the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS). RESULTS Data from all participants who completed either the 6-months or the 12-months follow-up (N=2064) were analysed. The majority of study participants rated the study as useful for their subjective mental wellbeing. This included talking more openly (68%) and understanding one’s mental health problems better (56%). While most participants (76%) found their assessment results useful, only a small proportion (15%) subsequently discussed them with a mental health professional, leading to only a small number of study participants receiving a new diagnosis (5%). Among those who were reviewed, new mood disorder diagnoses were predicted by the digital algorithm with high sensitivity (above 70%), and nearly half of the newly-diagnosed participants also had a corresponding change in medication. Furthermore, participants’ subjective wellbeing significantly improved over 12 months (baseline WEMWBS score: M=35.24, SD=8.11; 12-months WEMWBS score: M=41.19, SD=10.59). Significant positive predictors of follow-up subjective wellbeing included talking more openly, exercising more and having been reviewed by a psychiatrist. CONCLUSIONS Our results suggest that completing an online mental health assessment and receiving personalised psychoeducation is associated with subjective mental health improvements, facilitated by increased self-awareness and subsequent utilisation of self-help interventions. Integrating online mental health assessments within primary and/or secondary care services could benefit patients further and expedite earlier diagnosis and effective treatment. INTERNATIONAL REGISTERED REPORT RR2-10.2196/18453