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Microorganisms can be found almost anywhere, including in and on the human body. The collection of microorganisms associated with a certain location is called a microbiota, with its collective genetic material referred to as the microbiome. The largest population of microorganisms on the human body resides in the gastrointestinal tract; thus, it is not surprising that the most investigated human microbiome is the human gut microbiome. On average, the gut hosts microbes from more than 60 genera and contains more cells than the human body. The human gut microbiome has been shown to influence many aspects of host health, including more recently the brain.Several modes of interaction between the gut and the brain have been discovered, including via the synthesis of metabolites and neurotransmitters, activation of the vagus nerve, and activation of the immune system. A growing body of work is implicating the microbiome in a variety of psychological processes and neuropsychiatric disorders. These include mood and anxiety disorders, neurodevelopmental disorders such as autism spectrum disorder and schizophrenia, and even neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Moreover, it is probable that most psychotropic medications have an impact on the microbiome.Here, an overview will be provided for the bidirectional role of the microbiome in brain health, age-associated cognitive decline, and neurological and psychiatric disorders. Furthermore, a primer on the common microbiological and bioinformatics techniques used to interrogate the microbiome will be provided. This review is meant to equip the reader with a primer to this exciting research area that is permeating all areas of biological psychiatry research.

The binding specificities of an individual’s antibody repertoire contain a wealth of biological information. They harbor evidence of environmental exposures, allergies, ongoing or emerging autoimmune disease processes, and responses to immunomodulatory therapies, for example. Highly multiplexed methods to comprehensively interrogate antibody-binding specificities have therefore emerged in recent years as important molecular tools. Here, we provide a detailed protocol for performing ‘phage immunoprecipitation sequencing’ (PhIP-Seq), which is a powerful method for analyzing antibody-repertoire binding specificities with high throughput and at low cost. The methodology uses oligonucleotide library synthesis (OLS) to encode proteomic-scale peptide libraries for display on bacteriophage. These libraries are then immunoprecipitated, using an individual’s antibodies, for subsequent analysis by high-throughput DNA sequencing. We have used PhIP-Seq to identify novel self-antigens associated with autoimmune disease, to characterize the self-reactivity of broadly neutralizing HIV antibodies, and in a large international cross-sectional study of exposure to hundreds of human viruses. Compared with alternative array-based techniques, PhIP-Seq is far more scalable in terms of sample throughput and cost per analysis. Cloning and expression of recombinant proteins are not required (versus protein microarrays), and peptide lengths are limited only by DNA synthesis chemistry (up to 90-aa (amino acid) peptides versus the typical 8- to 12-aa length limit of synthetic peptide arrays). Compared with protein microarrays, however, PhIP-Seq libraries lack discontinuous epitopes and post-translational modifications. To increase the accessibility of PhIP-Seq, we provide detailed instructions for the design of phage-displayed peptidome libraries, their immunoprecipitation using serum antibodies, deep sequencing–based measurement of peptide abundances, and statistical determination of peptide enrichments that reflect antibody–peptide interactions. Once a library has been constructed, PhIP-Seq data can be obtained for analysis within a week.

Adhesive joining has the severe limitation that damages/defects developed in the bondline are difficult to assess. Conventional non-destructive examination (NDE) techniques are adequate to reveal disbonding defects in fabrication and delamination near the end of service life but are not helpful in detecting and monitoring in-service degradation of the joint. Several techniques suitable for long-term joint integrity monitoring are proposed. Fiber Bragg grating (FBG) sensors embedded in the joint are one of the promising candidates. It has the advantages of being close to the damage and immune to environmental attack and electromagnetic interference. Damage and disbonding inside an adhesive joint will give rise to a non-uniform strain field that may bring about peak splitting and chirping of the FBG spectrum. It is shown that the evolution of the full spectral responses can closely reveal the development of damages inside the adhesive joints during tensile and fatigue failures. However, recording and comparing the successive full spectra in the course of damage is tedious and can be subjective. An energy modulation interrogation technique is proposed using a pair of tunable optical filters. Changes in the full FBG spectral responses are modulated by the filters and converted into a conveniently measurable voltage output by photodiodes. Monitoring damage development can then be easily automated, and the technique is well-suited for practical applications. Filter spectrum width of 5 nm and initial overlap with the FBG spectrum to give 40% of the maximum output voltage is found to be optimal for measurement. The technique is tested on embedded FBGs from different adhesive lap-joint specimens and successfully reflected the severity of changes in the full spectral shapes during the course of tensile failure. Moreover, the trends in these PD outputs corroborate with the V value previously proposed to describe the qualitative change in FBG spectral shape.

Conventional optical fiber temperature/strain sensors often have to make compromises between the resolution and the dynamic range. Here we present a new method that meets the measurement requirements for both high resolution and large dynamic range. A high-quality optical fiber Fabry-Perot Interferometer (FPI) constructed using a pair of chirped fiber Bragg gratings is employed as the sensor and a dual-mode direct spectrum interrogation method is proposed to identify the small drift of external temperature or strain. As a proof-of-concept illustration, a temperature resolution of 0.2 °C within 30–130 °C is demonstrated. For strain sensing, the resolution can be 10 µε within 0–1000 µε. The measurement resolution can be improved further by routinely increasing the reflectivity of the CFBG and the cavity length and the sensor can also be mass-produced. This new sensing schema not only resolves the conflict between the resolution and the dynamic range of fiber-optic temperature/strain sensors but can also be extended to other sensors and measurands.

To interrogate the pathogenesis of intrauterine growth restriction (IUGR) and apply Artificial Intelligence (AI) techniques to multi-platform i.e. nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) based metabolomic analysis for the prediction of IUGR. MS and NMR based metabolomic analysis were performed on cord blood serum from 40 IUGR (birth weight < 10th percentile) cases and 40 controls. Three variable selection algorithms namely: Correlation-based feature selection (CFS), Partial least squares regression (PLS) and Learning Vector Quantization (LVQ) were tested for their diagnostic performance. For each selected set of metabolites and the panel consists of metabolites common in three selection algorithms so-called overlapping set (OL), support vector machine (SVM) models were developed for which parameter selection was performed busing 10-fold cross validations. Area under the receiver operating characteristics curve (AUC), sensitivity and specificity values were calculated for IUGR diagnosis. Metabolite set enrichment analysis (MSEA) was performed to identify which metabolic pathways were perturbed as a direct result of IUGR in cord blood serum. All selected metabolites and their overlapping set achieved statistically significant accuracies in the range of 0.78-0.82 for their optimized SVM models. The model utilizing all metabolites in the dataset had an AUC = 0.91 with a sensitivity of 0.83 and specificity equal to 0.80. CFS and OL (Creatinine, C2, C4, lysoPC.a.C16.1, lysoPC.a.C20.3, lysoPC.a.C28.1, PC.aa.C24.0) showed the highest performance with sensitivity (0.87) and specificity (0.87), respectively. MSEA revealed significantly altered metabolic pathways in IUGR cases. Dysregulated pathways include: beta oxidation of very long fatty acids, oxidation of branched chain fatty acids, phospholipid biosynthesis, lysine degradation, urea cycle and fatty acid metabolism. A systematically selected panel of metabolites was shown to accurately detect IUGR in newborn cord blood serum. Significant disturbance of hepatic function and energy generating pathways were found in IUGR cases.

Timely diagnosis of tuberculosis disease is critical for positive patient outcomes, yet potentially millions go undiagnosed or unreported each year. Sputum is widely used as the testing input, but limited by its complexity, heterogeneity, and sourcing problems. Finding methods to interrogate noninvasive, non-sputum clinical specimens is indispensable to improving access to tuberculosis diagnosis and care. In this work, economical plasmonic gratings were used to analyze tuberculosis biomarker lipoarabinomannan (LAM) from clinical urine samples by single molecule fluorescence assay (FLISA) and compared with gold standard sputum GeneXpert MTB/ RIF, culture, and reference ELISA testing results. In this study, twenty sputum and urine sample sets were selected retrospectively from a repository of HIV-negative patient samples collected before initiation of anti-tuberculosis therapy. GeneXpert MTB/RIF and culture testing of patient sputum confirmed the presence or absence of pulmonary tuberculosis while all patient urines were reference ELISA LAM-negative. Plasmonic gratings produced by low-cost soft lithography were bound with anti-LAM capture antibody, incubated with patient urine samples, and biotinylated detection antibody. Fluorescently labeled streptavidin revealed single molecule emission by epifluorescence microscope. Using a 1 fg/mL baseline for limit of detection, single molecule FLISA demonstrated good qualitative agreement with gold standard tests on 19 of 20 patients, including accurately predicting the gold-standard-negative patients, while one gold-standard-positive patient produced no observable LAM in urine. Single molecule FLISA by plasmonic grating demonstrated the ability to quantify tuberculosis LAM from complex urine samples of patients from a high endemic setting with negligible interference from the complex media itself. Moreover, agreement with patient diagnoses by gold standard testing suggests that single molecule FLISA could be used as a highly sensitive test to diagnose tuberculosis noninvasively.

Background False confessions are often the product of an interrogation process, and the method by which an interrogation is conducted likely affects both the rate of truthful confessions and false confessions. An optimal interrogation method will maximize the former and minimize the latter. Objectives The current study was a partial update and extension of Meissner and colleagues' (2012) prior Campbell systematic review titled Interview and Interrogation Methods and their Effects on True and False Confessions. Our objective was to assess the effects of interrogation approach on the rates of true and false confessions for criminal (mock) suspects. Search Methods PsycINFO, Criminal Justice s, and 15 other databases were searched starting October 20, 2022, with the final search conducted on May 23, 2023; together with reference checking, citation searching, and contact with authors to identify additional studies. Selection Criteria All eligible studies experimentally manipulated interrogation approach (i.e., accusatorial, information‐gathering, or direct questioning) were conducted with mock suspects accused of wrongdoing where ground truth was known, and included information about confession rates. Data Collection and Analysis We used standard methodological procedures expected by The Campbell Collaboration for our selection of studies and data collection. However, we developed our own risk of bias items and analyzed our data using network meta‐analysis methods. Data were synthesized via random‐effects network meta‐analysis based on the logged odds ratio. Main Results Across the 27 research articles that provided statistical information sufficient to calculate an effect size, 29 individual studies provided a total of 81 effect sizes. Most studies were conducted with college students in the United States. Overall, our risk of bias assessment indicated that authors generally adhered to double‐blind procedures and avoided selective reporting of outcomes. Of note, however, it was often unclear how violations of the randomization process were dealt with. For true confessions, there were 12 studies estimating the effect between accusatorial and direct questioning, five estimating the effect between information‐gathering and direct questioning, and another five estimating the effect between accusatorial and information‐gathering. Compared to information‐gathering, on average, the accusatorial conditions observed fewer true confessions, although not statistically significant (combined OR = 0.55, 95% CI 0.29, 1.05). The largest effects were between information‐gathering and direct questioning, with the former producing significantly more true confessions on average (combined OR = 2.43, 95% CI 1.29, 4.59). This model showed good consistency between the direct and indirect effects. For false confessions, there were 20 studies estimating the effect between accusatorial and direct questioning, 4 studies estimating the effect between information‐gathering and direct questioning, and 7 estimating the effect between accusatorial and information‐gathering. On average, accusatorial conditions yielded more false confessions than direct questioning (combined OR = 3.03, 95% CI 1.83, 5.02) or information‐gathering (combined OR = 4.41, 95% CI 1.77, 10.97), both of which are statistically significant. In contrast, direct questioning and information‐gathering had roughly similar rates of false confessions with nonsignificant and small effects that slightly favored information‐gathering (combined OR = 0.69, 95% CI 0.27, 1.78). This model showed good consistency between the direct and indirect effects. For true confessions under a six‐node model, most of the direct, indirect, and combined network estimated mean odds ratios were not statistically significant. The only significant effects were for (1) information‐gathering versus direct questioning, with the former resulting in more true confessions (combined OR = 2.57, 95% CI 1.38, 4.78); and (2) accusatorial‐evidence ploy versus information‐gathering with the former resulting in fewer true confessions (combined OR = 0.37, 95% CI 0.16, 0.84). For false confessions under a six‐node model, we found significant effects for (1) accusatorial‐evidence ploys versus direct questioning, with the former resulting in more false confessions (combined OR = 2.98, 95% CI 1.59, 5.59); (2) accusatorial‐evidence ploys versus information‐gathering, with the former resulting in more false confessions (combined OR = 4.47, 95% CI 1.46, 13.68); (3) accusatorial‐other versus direct questioning, with the former resulting in more false confessions (combined OR = 3.12, 95% CI 1.37, 7.10); (4) accusatorial‐other versus information‐gathering, with the former resulting in more false confessions (combined OR = 4.67, 95% CI 1.61, 13.55); and (5) information‐gathering versus minimization, with the latter resulting in more false confessions (combined OR = 0.25, 95% CI = 0.08, 0.83). No other combined effects were significant. This model should be interpreted cautiously, however, as the Q statistics raised concerns regarding model consistency. Authors' Conclusions Overall, results support calls for reforming policies related to interviewing and interrogation practices to prohibit the use of accusatorial approaches and require the adoption of approaches that are science‐based.

Background Coercive measures continue to be an important topic in psychiatry. However, there is no proof of the effectiveness of the use of coercive measures, especially with suicidal people. For many years, attempts have been made to replace such measures with alternative noncoercive intervention options. This paper aims to clarify the situation of coercive measures, more precisely seclusions, in a general psychiatric hospital in Switzerland. It focuses on compulsory measures in patients with suicidal tendencies. Method In this single-centre retrospective cohort study, we used routinely collected medical data and performed qualitative analyses of medical histories to examine whether alternative measures to seclusion had been offered and/or provided to patients who had been secluded solely because of suicidality. Patients were aged 18–65 years and had received inpatient treatment at one of five adult acute care units at a general psychiatric hospital in Switzerland between September 2016 and December 2019. Results There were 5,935 inpatient treatment cases during the study period. Suicidality was rated as “acute” or “very high” at least once during the hospitalization in 219 (3.7%) cases. Of these, 60 were excluded from further analyses as they involved seclusion, but suicidality was not the exclusive indication for this measure. Coercive seclusion was imposed exclusively due to suicidality in 53 (33.3%) of the remaining 159 cases, whereas 106 (66.7%) cases were not secluded. The rates of seclusion among suicidal patients varied considerably between the hospital wards (13.0% to 55.3%). Suicidal patients with non-Swiss residence status and/or lacking language skills were particularly prone to be secluded. Additionally, alternative interventions were offered and provided significantly more frequently in the nonsecluded patients. Conclusions To avoid seclusion due to suicidal tendencies, it is necessary to have a general attitude of avoiding coercive measures at all costs. It is also important for qualified staff to be able to deal with challenging sociodemographic characteristics of patients such as foreign-language, which may require translators and intercultural interpreters.

The functionally tolerated sequence space of proteins can now be explored in an unprecedented way, owing to the expansion of genomic databases and the development of high-throughput methods to interrogate protein function. For signaling proteins, several recent studies have shown how the analysis of sequence variation leverages the available protein-structure information to provide new insights into specificity and allosteric regulation. In this Review, we discuss recent work that illustrates how this emerging approach is providing a deeper understanding of signaling proteins.