Traditional Diagnoses Research Articles

Using machine learning to derive neurobiological subtypes of general psychopathology in late childhood.

Traditional mental health diagnoses rely on symptom-based classifications. Yet this approach can oversimplify clinical presentations as diagnoses often do not adequately map onto neurobiological features. Alternatively, our study used structural imaging data and a semisupervised machine learning technique, heterogeneity through discriminative analysis, to identify neurobiological subtypes in 9- to 10-year-olds with high psychopathology endorsements (n = 9,027). Our model revealed two stable neurobiological subtypes (adjusted Rand index = 0.38). Subtype 1 showed smaller structural properties, elevated conduct problems and attention-deficit/hyperactivity disorder symptoms, and impaired cognitive performance compared to Subtype 2 and typically developing youth. Subtype 2 had larger structural properties, cognitive abilities comparable to typically developing youth, and elevated internalizing symptoms relative to Subtype 1 and typically developing youth. These subtypes remained stable in their neurobiological characteristics, cognitive ability, and associated psychopathology traits over time. Taken together, our data-driven approach uncovered evidence of neural heterogeneity as demonstrated by structural patterns that map onto divergent profiles of psychopathology symptoms and cognitive performance in youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The hierarchical taxonomy of psychopathology and the search for neurobiological substrates of mental illness: A systematic review and roadmap for future research.

Understanding the neurobiological mechanisms involved in psychopathology has been hindered by the limitations of categorical nosologies. The Hierarchical Taxonomy of Psychopathology (HiTOP) is an alternative dimensional system for characterizing psychopathology, derived from quantitative studies of covariation among diagnoses and symptoms. HiTOP provides more promising targets for clinical neuroscience than traditional psychiatric diagnoses and can facilitate cumulative integration of existing research. We systematically reviewed 164 human neuroimaging studies with sample sizes of 194 or greater that have investigated dimensions of psychopathology classified within HiTOP. Replicated results were identified for constructs at five different levels of the hierarchy, including the overarching p-factor, the externalizing superspectrum, the thought disorder and internalizing spectra, the distress subfactor, and the depression symptom dimension. Our review highlights the potential of dimensional clinical neuroscience research and the usefulness of HiTOP while also suggesting limitations of existing work in this relatively young field. We discuss how HiTOP can be integrated synergistically with neuroscience-oriented, transdiagnostic frameworks developed by the National Institutes of Health, including the Research Domain Criteria, Addictions Neuroclinical Assessment, and the National Institute on Drug Abuse's Phenotyping Assessment Battery, and how researchers can use HiTOP to accelerate clinical neuroscience research in humans and other species. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information

This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. Traditional diagnoses are based on strict measurements that do not account for the factors of variability and uncertainty of the actual data. In this article, we perform six different types of tests in this regard, and data have been collected during the period of 2021 to 2022 of 188 power transformer failures in the New KotLakhpat Lahore unit, whose voltage range is 132/66 kv and rating capacity is 40/50 MVA. In this case, a fuzzy logic-based scheme is developed based upon the membership function, a rule-based and defuzzification method that works with imprecision and the implementation of uncertainty in assessing the condition of transformer oils. Moisture, acidity, and a dissolved gas analysis indicator, along with other indication approaches such as interfacial tension, viscosity, and tangent delta measurement, are used to analyze the deterioration process in transformer oils. In the visual representation, oil samples with the following properties were first fuzzified: 19.9 mm2/s of viscosity, 0.453 mgKOH/g of acidity, 695 ppm of DGA, 20.8 mg/kg of moisture, 19.98 of IFT, and 4.35 × 100.14 of tangent delta. The output that was generated by software using the values entered into the parameters (HI and Age) after defuzzification is 45. Fuzzy logic serves as a concrete framework for transforming the diagnostics system and deterring the threats to the entire transformer’s health and reliability in the future. By using this technique, various faults were hypothetically and practically analyzed in a transformer to implement early detection technologies with the possibility to reduce maintenance costs and extend operational life up to 45 years. Various case studies indicate the effectiveness of fuzzy logic in comparison to traditional diagnostics.

Designing nanotheranostics with machine learning.

The inherent limits of traditional diagnoses and therapies have driven the development and application of emerging nanotechnologies for more effective and safer management of diseases, herein referred to as 'nanotheranostics'. Although many important technological successes have been achieved in this field, widespread adoption of nanotheranostics as a new paradigm is hindered by specific obstacles, including time-consuming synthesis of nanoparticles, incomplete understanding of nano-bio interactions, and challenges regarding chemistry, manufacturing and the controls required for clinical translation and commercialization. As a key branch of artificial intelligence, machine learning (ML) provides a set of tools capable of performing time-consuming and result-perception tasks, thus offering unique opportunities for nanotheranostics. This Review summarizes the progress and challenges in this emerging field of ML-aided nanotheranostics, and discusses the opportunities in developing next-generation nanotheranostics with reliable datasets and advanced ML models to offer better clinical benefits to patients.

Traditional clinical symptoms and signs: Kampo pattern diagnosis in modern gastrointestinal disease.

In traditional Japanese Kampo medicine, a profound anamnesis is completed by clinical examination. The resulting clinical image forms the basis of the patient's diagnosis pattern, including the recent mental, physical, and social contexts. Kampo questionnaires support pattern diagnosis and bridge traditional and Western medicine diagnoses. Traditional Kampo therapy is tailored to a specific body constitution, while Western medicine treatment is tailored to a specific disease. The aims of this study were to analyze whether traditional Kampo diagnosis is applicable to German patients and whether specific symptom patterns are characteristic for defined diseases. This study validates for the first time a Kampo questionnaire adapted for German patients. The analysis focuses on patients with gastrointestinal diseases, the main field for Kampo medicines. In total, we prospectively included 251 participants; of those, 58 were cancer patients (23.1%), 35 had Crohn's disease (13.9%), 18 had ulcerative colitis (7.2%), 17 had irritable bowel syndrome (6.8%), and 103 had other abdominal diseases (41%), as well as 20 German controls (8%). The patient population consisted of 144 female (57.4%) and 107 male (42.6%) participants. The median age was 65years. The disease duration (average: 211months) varied from 1month (cancer patient) to 540months (patient with Crohn's disease). The scores for questions on the state of mind were significantly higher in patients with inflammatory bowel disease (IBD) as well as irritable bowel syndrome (IBS)-in comparison to the tumor and control groups. This was reflected in questions about abdominal discomfort, appetite, fecal habits, and cold sensation. Accordingly, symptoms of Qi (i.e., vital energy) deficiency were mostly observed in patients with chronic diseases such as Crohn's disease and ulcerative colitis. Defined symptom combinations did not reflect conventional Western diagnosis. Our study results show that symptom patterns are independent of the underlying disease. They rather depict the individual patient within an individual time frame. Traditional Kampo questionnaires were found to be valid for the analysis of a patients' body constitution (sho) and serve as a guide for Kampo treatment. We propose that individual pattern diagnosis should be taken into account to help treatment individualization.

Multiplex Gastrointestinal Panel Testing in Hospitalized Patients With Acute Diarrhea in Thailand.

Multiplex gastrointestinal (GI) panel testing is widely used for outpatient diagnosis of diarrhea. However, the clinical practicality of multiplex testing in hospitalized diarrheal subjects has not yet been thoroughly elucidated. We enrolled hospitalized subjects with acute diarrhea. The subjects' stool samples were collected in triplicate; 1 sample was tested using traditional diagnoses, and the other 2 were tested using Allplex (AP) and FilmArray (FA) GI panel testing. Clinical data were reviewed and analyzed. Of the 199 subjects, 92 (46.5%) were male, and the mean age was 66.3 years. The median (interquartile range) onset of diarrhea was 6 (2--14) days after hospitalization. One hundred fifty-one patients (75.9%) had sepsis, and 166 (83.4%) had received prior or were receiving current antimicrobial therapy. Positive stool cultures were obtained from 4/89 (4.5%), and Clostridioides difficile toxin gene tests were positive in 14/188 (7.4%) patients. AP and FA multiplex tests were positive for GI pathogens in 49/199 (24.6%) and 40/199 (20.1%), respectively. The target most frequently detected by AP was Aeromonas spp. Both assays commonly detected enteropathogenic E. coli (EPEC), C. difficile toxin gene, and Salmonella spp.; neither assay detected pathogens in 75.4% and 79.9%. Fever (odds ratio [OR], 2.05; 95% CI, 1.08-3.88; P = .028), watery diarrhea (OR, 2.69; 95% CI, 1.25-5.80; P = .011), and antimicrobial therapy (OR, 2.60; 95% CI, 1.18-5.71; P = .018) were independent factors associated with the negative multiplex test result. Multiplex GI panel testing effectively detects enteric pathogens associated with diarrhea in hospitalized subjects. The etiology remains undiagnosed in >75% of cases. Factors contributing to negative test results should be considered before implementing the tests.

Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer's Disease Using 3D Comprehensive Visual Stimuli.

Alzheimer's Disease (AD) is a neurodegenerative disorder that causes a continuous decline in cognitive functions and eventually results in death. An early AD diagnosis is important for taking active measures to slow its deterioration. Traditional diagnoses are usually based on clinical experience, which is limited by several realistic factors. In this paper, we focus on exploiting deep learning techniques to diagnose AD based on eye-tracking behaviors. Visual attention, as a typical eye-tracking behavior, is of great clinical value in detecting cognitive abnormalities in AD patients. To better analyze the differences in visual attention between AD patients and normals, we first conducted a 3D comprehensive visual task on a noninvasive eye-tracking system to collect visual attention heatmaps. Then a multilayered comparison convolutional neural network (MC-CNN) is proposed to distinguish the visual attention differences between AD patients and normals. In MC-CNN, the multilayered feature representations of heatmaps were obtained by hierarchical residual blocks to better encode eye movement behaviors, which were further integrated into a distance vector to benefit the comprehensive visual task. From evaluation, MC-CNN can distinguish AD patients from normals with 0.84 accuracy, 0.86 recall, 0.82 precision, 0.83 F1-score and 0.90 area under the curve (AUC). The above results demonstrate the effectiveness of the proposed MC-CNN in AD diagnosis based on the comprehensive 3D visual task.

Shared and unique characteristics of metabolic syndrome in psychotic disorders: a review.

People with psychosis spectrum disorders (PSD) face an elevated risk of metabolic syndrome (MetS), which may reduce their life expectancy by nearly 20%. Pinpointing the shared and specific characteristics and clinical implications of MetS in PSD is crucial for designing interventions to reduce this risk, but an up-to-date review on MetS across the psychosis spectrum is lacking. This narrative review fills this gap by examining the clinical literature on characteristics and implications of MetS in both distinct PSD and transdiagnostically, i.e., across traditional categorical diagnoses, with a focus on psychiatric and cardio-metabolic management. We discuss common and specific characteristics of MetS in PSD, as well as factors contributing to MetS development in PSD patients, including unhealthy lifestyle factors, genetic predisposition, pro-inflammatory state, drugs consumption, antipsychotic medication, and psychotic symptoms. We highlight the importance of early identification and management of cardio-metabolic risk in PSD patients, as well as the existing gaps in the literature, for instance in the screening for MetS in younger PSD patients. We compare hypotheses-generating clinical associations and characteristics of MetS in different PSD, concluding by reviewing the existing recommendations and challenges in screening, monitoring, and managing MetS in PSD. Early identification and management of MetS are crucial to mitigate the long-term cardio-metabolic toll in PSD patients. Interventions should focus on healthy lifestyle and appropriate pharmacological and behavioral interventions. Further translational and clinical research is needed to develop targeted interventions and personalized treatment approaches for this vulnerable population, aiming at improving physical health and overall well-being.

Psychosis superspectrum II: neurobiology, treatment, and implications.

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Providing Prenatal Care in a Student Run Free Clinic

Background: Prenatal care is a cornerstone of maternal and child health. This paper describes the creation of a free prenatal clinic for uninsured families following recognition of a significant disparity in birth outcomes in Alachua County, Florida including: the development of essential community re- source collaborations, clinical operations in a dual aim patient care-medical education site, preliminary outcomes after one year of clinical operation, identified challenges, and next steps for our growing program.
 Methods: A retrospective chart review of all sixteen patients enrolled with the student run free prenatal clinic in its first year of clinical operation. Analysis included assessment of the prenatal care course using descriptive statistics. Specific dimensions assessed include timing of transition of care to a traditional obstetrics clinic, clinical findings and diagnoses identified at the prenatal clinic, and birth out- comes during the study period and report findings as descriptive statistics.
 Results: The clinic has demonstrated the ability to identify and treat numerous pathologies which may impact maternal-fetal morbidity and mortality. The clinic has seen very high rates of patient retention and has demonstrated successful transition of patients to higher levels of care when indicated. Finally, the clinical model provides an uncommon opportunity for medical and physician assistant students to care for patients throughout the first 32 weeks of pregnancy and receive additional training in point-of-care ultrasound, diagnostics, and medical decision making.
 Conclusion: While the small sample size limits the ability to assess the effectiveness of the prenatal clinic intervention, there are numerous promising features based on preliminary results.

Psychodynamic profiles of major depressive disorder and generalized anxiety disorder in China.

Traditional clinical diagnoses relying on symptoms may overlook latent factors that illuminate mechanisms and potentially guide treatment. The Operationalized Psychodynamic Diagnosis (OPD) system may compensate for symptom-based diagnosis by measuring psychodynamic profiles underlying mental disorders through conflicts and structure axes. However, OPD has not been widely adopted in China, and it remains unclear whether OPD can be used as an effective approach to distinguish between depression and anxiety. The current study aims to adopt the OPD system to investigate the psychodynamic profiles of major depressive disorder (MDD) and generalized anxiety disorder (GAD) in China, targeting patients with "pure" symptoms without comorbidity. We recruited 42 MDD patients, 32 GAD patients, and 31 healthy controls (HC), and assessed their self-report depression and anxiety symptoms, along with their underlying psychodynamic profiles through OPD interviews. Overall, both MDD and GAD patients showed more prominent conflict issues and lower levels of structure than HC. The MDD and GAD groups yielded different conflict profiles and conflict processing modes when processing their second conflicts. Importantly, the multi-dimensional psychodynamic profiles achieved machine learning classification of clinical groups with an accuracy of 0.84, supporting successful distinction of MDD and GAD patients. In conclusion, the OPD demonstrated sensitivity in revealing distinct psychodynamic profiles underlying "pure" depression and anxiety clinical populations in China. This work calls for future incorporation of OPD as a tool to investigate psychodynamic formulations underlying mental disorders, compensating for traditional symptom-based diagnostic approaches to guide precise individualized interventions.

Psychosis superspectrum I: Nosology, etiology, and lifespan development.

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

Efficacy of combination therapy with unkeito and boiogito for menopausal arthralgia: A retrospective observational study.

Arthralgia affects menopausal patients. Here, we report a retrospective observational study evaluating the therapeutic efficacy of a combination of unkeito and boiogito for menopausal arthralgia. Patients treated with a combination of unkeito and boiogito for menopausal arthralgia between April 2020 and October 2022 at three Japanese Kampo outpatient clinics were retrospectively examined. Treatment effectiveness was determined based on the patient's description of pain. Adverse events associated with this treatment regimen were also recorded. The study design was approved by the Tokai University Ethics Committee (Approval number: 22R196). This study was conducted by retrospectively analysing the medical records of patients who attended the three medical facilities. All patients received Kampo medicines based on traditional medical diagnoses. Outpatients with a diagnosis of menopausal arthralgia were selected, and information on those who were treated with a combination of unkeito and boiogito was collected. The age, height, and weight of all patients are represented as the mean ± standard deviation. Statistical analyses were not performed in this study as there was no comparison group. During the study period, nine patients with menopausal arthralgia received the unkeito and boiogito combination. Four patients showed a "significant" response to the combination treatment, four showed an "effective" response, and one patient showed an "ineffective" response. One patient reported headache as an adverse event. The combination of unkeito and boiogito may be effective in the treatment of menopausal arthralgia.

Effectiveness of auriculotherapy in anxiety according to traditional diagnoses

Effectiveness of auriculotherapy in anxiety according to traditional diagnoses

Semi-automated visualization method for visual inspection of buildings on BIM using 3D point cloud

Regular diagnosis of a building can identify structural safety and latent hazards and establish efficient maintenance strategies. Traditional diagnoses are based on personal perspectives or knowledge of experts; therefore, they are laborious, time-consuming, and subjective. Moreover, the results may be unreliable. In addition, an undefined data format makes its practical use difficult. This study proposes a visualized semi-automated approach to extract building condition data and integrate them with BIM using Dynamo. The proposed framework uses Python code to improve efficiency when extracting coordinates. First, 3D point cloud data on the external walls of buildings obtained using a laser scanner are processed, and the relevant information, such as coordinates, is extracted. Second, the BIM model is implemented based on a point cloud using supplementary modeling tools. Finally, the extracted defects are modeled as new objects, and each BIM object is colored according to the modified criteria. To validate the feasibility of the proposed method, it was applied to actual buildings, improving the efficiency and accuracy of building inspections. This is expected to facilitate a reduction in building maintenance work and the identification of deterioration patterns.

Functional Neurological Disorder in Saudi Arabia: An Update.

Functional neurological disorder (FND) is characterized by neurological symptoms that lack congruence with traditional neurological diagnoses. Historically viewed through a Freudian psychoanalytic lens, FND has been conceptualized as a purely psychogenic disorder. However, the contemporary biopsychosocial perspective on FND emphasizes contributions of cognitive and neural circuit dysfunctionand the disabling and involuntary nature of the illness. In Saudi Arabia, evidence suggests the prevalence of FND is significant. However, clinical programs and research focused on FND have been lacking. Studies from the region indicate that practitioners may have outdated views of FND. To address this, this narrative review provides an updated perspective on FND that is relevant to Saudi Arabia and the region. It delves into the evolving perception of FND, its underlying pathophysiology, risk factors, clinical presentations, and recent diagnostic and management advances. Unique features of FND in Saudi Arabia may include a significant role for family disputes as a risk factor, prevalent supernatural perceptions of FND, high prevalence of somatization, and cognitive dysfunction, and a potential favorable prognosis. The article concludes by providing the following recommendations related to FND in Saudi Arabia and the region: i) building educational programs to update clinicians about contemporary biopsychosocial perspectives on FND; ii) emphasizing a positive diagnostic approach based on clinical findings in FND; iii) instituting multidisciplinary programs to care for FND patients; iv) supporting systematic research efforts to explore culture-specific FND risk factors, patient outcome measures, and attitudes toward the disorder; v) developing national FND clinical practice guidelines; and vi) launching awareness campaigns to reduce FND stigma.

Transdiagnostic analysis of adverse childhood experiences and their association with psychopathology–A TRANS-D conform study

Transdiagnostic approaches challenge traditional psychiatric classification systems. Adverse childhood experiences (ACE) represent a transdiagnostic risk factor for psychopathology with dose dependency. As different qualities of ACE typically co-occur, we identified ACE patterns to assess their power for predicting psychopathology compared to traditional diagnoses. Following TRANS-D guidelines, we categorized participants (N=360) with persistent depressive disorder (PDD), borderline personality disorder (BPD), or healthy control status (HC) into subcategories defined by ACE pattern, using the Childhood Trauma Questionnaire (CTQ). Improvement of the transdiagnostic vs. diagnostic approach in predicting psychopathology was evaluated in a cross-validated predictive modeling framework focusing on the clinical sample of PDD and BPD patients. Results were externally validated in another transdiagnostic sample (N=138). Seven pattern-based subcategories with distinct ACE profiles were identified in the primary sample and replicated in the validation sample. Patterns cut across diagnostic groups. Predictive modeling showed that diagnoses could not predict depressive symptoms and loneliness. Transdiagnostic constructs systematically predicted all measures. This study showcases ACE as a promising construct for transdiagnostic research. Our data-driven framework identified robust ACE subcategories mapping onto general and interpersonal psychopathology. Patterns of CTQ-based information may provide an approach to integrating information on co-occurring ACE to inform diagnostics and treatment.

Transdiagnostic MRI markers of psychopathology following traumatic brain injury: a systematic review and network meta-analysis protocol

IntroductionPsychopathology following traumatic brain injury (TBI) is a common and debilitating consequence that is often associated with reduced functional and psychosocial outcomes. There is a lack of evidence regarding the...

Molecular Identification of Acrossocheilus jishouensis (Teleostei: Cyprinidae) and Its Complete Mitochondrial Genome.

Molecular identification, such as DNA barcoding, is a useful tool that is widely applied in distinguishing species. To identify the cyprinid Acrossocheilus jishouensis, which was previously known to be restricted to only its type locality, we conducted molecular identification of this species based on 23 samples in five localities. Molecular identification based on the mitochondrial COI gene sequence showed that the morphologically similar samples from the five populations were all A. jishouensis, as the mean genetic distances between populations were very small (0.1-1.6%); thus, the distribution of this species was substantially expanded. The whole mitochondrial genome of one sample was also assembled, which was 16,594bp in length and consisted of 13 protein-coding genes (PCGs), two rRNA genes, 22 tRNA genes, and one control region. All PCGs began with ATG except the COI gene, which started with GTG; seven PCGs used the complete stop codon TAA, while four terminated in T(AA) and two ended with TAG. The overall base composition reflected a higher proportion of A+T than G+C and a positive AT-skew and negative GC-skew pattern except for the opposite in ND6. Phylogenetic relationships inferred using BI and ML methods revealed that both Acrossocheilus and Onychostoma were nonmonophyletic, which indicated that the traditional diagnoses between these two genera need to be assessed further. The results of this study not only expanded the known distribution ranges of A. jishouensis, but also provided a valuable data resource for future molecular and evolutionary studies of Acrossocheilus and other cyprinids in Barbinae.

Genomic newborn screening for rare diseases.

Rare diseases are a leading cause of infant mortality and lifelong disability. To improve outcomes, timely diagnosis and effective treatments are needed. Genomic sequencing has transformed the traditional diagnostic process, providing rapid, accurate and cost-effective genetic diagnoses to many. Incorporating genomic sequencing into newborn screening programmes at the population scale holds the promise of substantially expanding the early detection of treatable rare diseases, with stored genomic data potentially benefitting health over a lifetime and supporting further research. As several large-scale newborn genomic screening projects launch internationally, we review the challenges and opportunities presented, particularly the need to generate evidence of benefit and to address the ethical, legal and psychosocial issues that genomic newborn screening raises.