Identification and validation of supervariants reveal novel loci associated with human white matter microstructure.

As an essential part of the central nervous system, white matter coordinates communications between different brain regions and is related to a wide range of neurodegenerative and neuropsychiatric disorders. Previous genome-wide association studies (GWASs) have uncovered loci associated with white matter microstructure. However, GWASs suffer from limited reproducibility and difficulties in detecting multi-single-nucleotide polymorphism (multi-SNP) and epistatic effects. In this study, we adopt the concept of supervariants, a combination of alleles in multiple loci, to account for potential multi-SNP effects. We perform supervariant identification and validation to identify loci associated with 22 white matter fractional anisotropy phenotypes derived from diffusion tensor imaging. To increase reproducibility, we use United Kingdom (UK) Biobank White British (n = 30,842) data for discovery and internal validation, and UK Biobank White but non-British (n = 1927) data, Europeans from the Adolescent Brain Cognitive Development study (n = 4399) data, and Europeans from the Human Connectome Project (n = 319) data for external validation. We identify 23 novel loci on the discovery set that have not been reported in the previous GWASs on white matter microstructure. Among them, three supervariants on genomic regions 5q35.1, 8p21.2, and 19q13.32 have P-values lower than 0.05 in the meta-analysis of the three independent validation data sets. These supervariants contain genetic variants located in genes that have been related to brain structures, cognitive functions, and neuropsychiatric diseases. Our findings provide a better understanding of the genetic architecture underlying white matter microstructure.

A comprehensive patient-specific prediction model for temporomandibular joint osteoarthritis progression.

Temporomandibular joint osteoarthritis (TMJ OA) is a prevalent degenerative disease characterized by chronic pain and impaired jaw function. The complexity of TMJ OA has hindered the development of prognostic tools, posing a significant challenge in timely, patient-specific management. Addressing this gap, our research employs a comprehensive, multidimensional approach to advance TMJ OA prognostication. We conducted a prospective study with 106 subjects, 74 of whom were followed up after 2 to 3 y of conservative treatment. Central to our methodology is the development of an innovative, open-source predictive modeling framework, the Ensemble via Hierarchical Predictions through Nested cross-validation tool (EHPN). This framework synergistically integrates 18 feature selection, statistical, and machine learning methods to yield an accuracy of 0.87, with an area under the ROC curve of 0.72 and an F1 score of 0.82. Our study, beyond technical advancements, emphasizes the global impact of TMJ OA, recognizing its unique demographic occurrence. We highlight key factors influencing TMJ OA progression. Using SHAP analysis, we identified personalized prognostic predictors: lower values of headache, lower back pain, restless sleep, condyle high gray level-GL-run emphasis, articular fossa GL nonuniformity, and long-run low GL emphasis; and higher values of superior joint space, mouth opening, saliva Vascular-endothelium-growth-factor, Matrix-metalloproteinase-7, serum Epithelial-neutrophil-activating-peptide, and age indicate recovery likelihood. Our multidimensional and multimodal EHPN tool enhances clinicians' decision-making, offering a transformative translational infrastructure. The EHPN model stands as a significant contribution to precision medicine, offering a paradigm shift in the management of temporomandibular disorders and potentially influencing broader applications in personalized healthcare.

Peptidyl-prolyl isomerase Cyclophilin71 promotes SERRATE phase separation and miRNA processing in Arabidopsis.

MicroRNAs (miRNAs) play an important role in gene regulation. In Arabidopsis, mature miRNAs are processed from primary miRNA transcripts by the Dicing complex that contains Dicer-like 1 (DCL1), SERRATE (SE), and Hyponastic Leaves 1 (HYL1). The Dicing complex can form nuclear dicing bodies (D-bodies) through SE phase separation. Here, we report that Cyclophilin71 (CYP71), a peptidyl-prolyl isomerase (PPIase), positively regulates miRNA processing. We show that CYP71 directly interacts with SE and enhances its phase separation, thereby promoting the formation of D-body and increasing the activity of the Dicing complex. We further show that the PPIase activity is important for the function of CYP71 in miRNA production. Our findings reveal orchestration of miRNA processing by a cyclophilin protein and suggest the involvement of peptidyl-prolyl cis-trans isomerization, a structural mechanism, in SE phase separation and miRNA processing.

FPLS-DC: functional partial least squares through distance covariance for imaging genetics.

MOTIVATION: Imaging genetics integrates imaging and genetic techniques to examine how genetic variations influence the function and structure of organs like the brain or heart, providing insights into their impact on behavior and disease phenotypes. The use of organ-wide imaging endophenotypes has increasingly been used to identify potential genes associated with complex disorders. However, analyzing organ-wide imaging data alongside genetic data presents two significant challenges: high dimensionality and complex relationships. To address these challenges, we propose a novel, nonlinear inference framework designed to partially mitigate these issues. RESULTS: We propose a functional partial least squares through distance covariance (FPLS-DC) framework for efficient genome wide analyses of imaging phenotypes. It consists of two components. The first component utilizes the FPLS-derived base functions to reduce image dimensionality while screening genetic markers. The second component maximizes the distance correlation between genetic markers and projected imaging data, which is a linear combination of the FPLS-basis functions, using simulated annealing algorithm. In addition, we proposed an iterative FPLS-DC method based on FPLS-DC framework, which effectively overcomes the influence of inter-gene correlation on inference analysis. We efficiently approximate the null distribution of test statistics using a gamma approximation. Compared to existing methods, FPLS-DC offers computational and statistical efficiency for handling large-scale imaging genetics. In real-world applications, our method successfully detected genetic variants associated with the hippocampus, demonstrating its value as a statistical toolbox for imaging genetic studies. AVAILABILITY AND IMPLEMENTATION: The FPLS-DC method we propose opens up new research avenues and offers valuable insights for analyzing functional and high-dimensional data. In addition, it serves as a useful tool for scientific analysis in practical applications within the field of imaging genetics research. The R package FPLS-DC is available in Github: https://github.com/BIG-S2/FPLSDC.

The interaction effects of age, APOE and common environmental risk factors on human brain structure.

Mounting evidence suggests considerable diversity in brain aging trajectories, primarily arising from the complex interplay between age, genetic, and environmental risk factors, leading to distinct patterns of micro- and macro-cerebral aging. The underlying mechanisms of such effects still remain unclear. We conducted a comprehensive association analysis between cerebral structural measures and prevalent risk factors, using data from 36,969 UK Biobank subjects aged 44-81. Participants were assessed for brain volume, white matter diffusivity, Apolipoprotein E (APOE) genotypes, polygenic risk scores, lifestyles, and socioeconomic status. We examined genetic and environmental effects and their interactions with age and sex, and identified 726 signals, with education, alcohol, and smoking affecting most brain regions. Our analysis revealed negative age-APOE-ε4 and positive age-APOE-ε2 interaction effects, respectively, especially in females on the volume of amygdala, positive age-sex-APOE-ε4 interaction on the cerebellar volume, positive age-excessive-alcohol interaction effect on the mean diffusivity of the splenium of the corpus callosum, positive age-healthy-diet interaction effect on the paracentral volume, and negative APOE-ε4-moderate-alcohol interaction effects on the axial diffusivity of the superior fronto-occipital fasciculus. These findings highlight the need of considering age, sex, genetic, and environmental joint effects in elucidating normal or abnormal brain aging.

Mapping developmental regionalization and patterns of cortical surface area from 29 post-menstrual weeks to 2 years of age.

Surface area of the human cerebral cortex expands extremely dynamically and regionally heterogeneously from the third trimester of pregnancy to 2 y of age, reflecting the spatial heterogeneity of the underlying microstructural and functional development of the cerebral cortex. However, little is known about the developmental patterns and regionalization of cortical surface area during this critical stage, due to the lack of high-quality imaging data and accurate computational tools for pediatric brain MRI data. To fill this critical knowledge gap, by leveraging 1,037 high-quality MRI scans with the age between 29 post-menstrual weeks and 24 mo from 735 pediatric subjects in two complementary datasets, i.e., the Baby Connectome Project (BCP) and the developing Human Connectome Project (dHCP), and state-of-the-art dedicated image-processing tools, we unprecedentedly parcellate the cerebral cortex into a set of distinct subdivisions purely according to the developmental patterns of the cortical surface. Our discovered developmentally distinct subdivisions correspond well to structurally and functionally meaningful regions and reveal spatially contiguous, hierarchical, and bilaterally symmetric patterns of early cortical surface expansion. We also show that high-order association subdivisions, where cortical folds emerge later during prenatal stages, undergo more dramatic cortical surface expansion during infancy, compared with the central regions, especially the sensorimotor and insula cortices, thus forming a distinct central-pole division in early cortical surface expansion. These results provide an important reference for exploring and understanding dynamic early brain development in health and disease.

Label-free single-particle imaging approach for ultra-rapid detection of pathogenic bacteria in clinical samples.

Rapid detection of pathogenic bacteria within a few minutes is the key to control infectious disease. However, rapid detection of pathogenic bacteria in clinical samples is quite a challenging task due to the complex matrix, as well as the low abundance of bacteria in real samples. Herein, we employ a label-free single-particle imaging approach to address this challenge. By tracking the scattering intensity variation of single particles in free solution, the morphological heterogeneity can be well identified with particle size smaller than the diffraction limit, facilitating the morphological identification of single bacteria from a complex matrix in a label-free manner. Furthermore, the manipulation of convection in free solution enables the rapid screening of low-abundance bacteria in a small field of view, which significantly improves the sensitivity of single-particle detection. As a proof of concept demonstration, we are able to differentiate the group B streptococci (GBS)-positive samples within 10 min from vaginal swabs without using any biological reagents. This is the most rapid and low-cost method to the best of our knowledge. We believe that such a single-particle imaging approach will find wider applications in clinical diagnosis and disease control due to its high sensitivity, rapidity, simplicity, and low cost.

SIRT5 exacerbates eosinophilic chronic rhinosinusitis by promoting polarization of M2 macrophage.

BACKGROUND: Previous studies implied that local M2 polarization of macrophage promoted mucosal edema and exacerbated TH2 type inflammation in chronic rhinosinusitis with nasal polyps (CRSwNP). However, the specific pathogenic role of M2 macrophages and the intrinsic regulators in the development of CRS remains elusive. OBJECTIVE: We sought to investigate the regulatory role of SIRT5 in the polarization of M2 macrophages and its potential contribution to the development of CRSwNP. METHODS: Real-time reverse transcription-quantitative PCR and Western blot analyses were performed to examine the expression levels of SIRT5 and markers of M2 macrophages in sinonasal mucosa samples obtained from both CRS and control groups. Wild-type and Sirt5-knockout mice were used to establish a nasal polyp model with TH2 inflammation and to investigate the effects of SIRT5 in macrophage on disease development. Furthermore, in vitro experiments were conducted to elucidate the regulatory role of SIRT5 in polarization of M2 macrophages. RESULTS: Clinical investigations showed that SIRT5 was highly expressed and positively correlated with M2 macrophage markers in eosinophilic polyps. The expression of SIRT5 in M2 macrophages was found to contribute to the development of the disease, which was impaired in Sirt5-deficient mice. Mechanistically, SIRT5 was shown to enhance the alternative polarization of macrophages by promoting glutaminolysis. CONCLUSIONS: SIRT5 plays a crucial role in promoting the development of CRSwNP by supporting alternative polarization of macrophages, thus providing a potential target for CRSwNP interventions.

Mapping Genetic Topography of Cortical Thickness and Surface Area in Neonatal Brains.

Adult twin neuroimaging studies have revealed that cortical thickness (CT) and surface area (SA) are differentially influenced by genetic information, leading to their spatially distinct genetic patterning and topography. However, the postnatal origins of the genetic topography of CT and SA remain unclear, given the dramatic cortical development from neonates to adults. To fill this critical gap, this study unprecedentedly explored how genetic information differentially regulates the spatial topography of CT and SA in the neonatal brain by leveraging brain magnetic resonance (MR) images from 202 twin neonates with minimal influence by the complicated postnatal environmental factors. We capitalized on infant-dedicated computational tools and a data-driven spectral clustering method to parcellate the cerebral cortex into a set of distinct regions purely according to the genetic correlation of cortical vertices in terms of CT and SA, respectively, and accordingly created the first genetically informed cortical parcellation maps of neonatal brains. Both genetic parcellation maps exhibit bilaterally symmetric and hierarchical patterns, but distinct spatial layouts. For CT, regions with closer genetic relationships demonstrate an anterior-posterior (A-P) division, while for SA, regions with greater genetic proximity are typically within the same lobe. Certain genetically informed regions exhibit strong similarities between neonates and adults, with the most striking similarities in the medial surface in terms of SA, despite their overall substantial differences in genetic parcellation maps. These results greatly advance our understanding of the development of genetic influences on the spatial patterning of cortical morphology.SIGNIFICANCE STATEMENT Genetic influences on cortical thickness (CT) and surface area (SA) are complex and could evolve throughout the lifespan. However, studies revealing distinct genetic topography of CT and SA have been limited to adults. Using brain structural magnetic resonance (MR) images of twins, we unprecedentedly discovered the distinct genetically-informed parcellation maps of CT and SA in neonatal brains, respectively. Each genetic parcellation map comprises a distinct spatial layout of cortical regions, where vertices within the same region share high genetic correlation. These genetic parcellation maps of CT and SA of neonates largely differ from those of adults, despite their highly remarkable similarities in the medial cortex of SA. These discoveries provide important insights into the genetic organization of the early cerebral cortex development.

Entrapment and Reactivation of Polysulfides in Conductive Amphiphilic Covalent Organic Frameworks Enabling Superior Capacity and Stability of Lithium-Sulfur Batteries.

Inhibiting the shuttle of polysulfides is of great significance for promoting the practical application of lithium-sulfur batteries (LSBs). Here, an imine-linked covalent organic framework@carbon nanotube (COF@CNT) interlayer composed of triazine and boroxine rings is constructed between the sulfur cathode and the separator for polysulfides reception and reutilization. The introduction of CNT imparts the conductor characteristic to the interlayer attributed to electron tunneling in thin COF shell, and creates a hierarchical porous architecture for accommodating polysulfides. The uniform distribution of amphiphilic adsorption sites in COF microporous structure not only enables efficient entrapment of polysulfides while allowing the penetration of Li+ ions, but also provides a stable electrocatalytic channel for bidirectional conversion of active sulfur to achieve the substantially improved capacity and stability. The interlayer-incorporated LSBs deliver an ultrahigh capacity of 1446 mA g-1 at 0.1C and an ultralow capacity decay rate of 0.019% at 1C over 1500 cycles. Even at an electrolyte/sulfur ratio of 6 µL mg-1, an outstanding capacity of 995 mAh g-1 and capacity retention of 74.1% over 200 cycles at 0.2C are obtained. This work offers a compelling polysulfides entrapment and reactivation strategy for stimulating the study on ultra-stable LSBs.

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development.

INTRODUCTION: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention. METHODS: This study included 2,288 participants with normal cognitive function from the Ma'anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level. RESULTS: The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773-0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults. CONCLUSION: The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Elevated DAS28-ESR in patients with rheumatoid arthritis who have comorbid fibromyalgia is associated more with tender joint counts than with patient global assessment or swollen joint counts: implications for assessment of inflammatory activity.

OBJECTIVES: More than 20% of rheumatoid arthritis (RA) patients have comorbid fibromyalgia (FM+), which may elevate DAS28-ESR (disease activity score 28-erythrocyte sedimentation rate) and other indices, resulting in challenges to assess inflammatory disease activity. Although several reports indicate that elevated patient global assessment (PATGL) may elevate DAS28 in the absence of inflammatory activity, less information is available concerning the other three components, tender joint count (TJC), swollen joint count (SJC), and erythrocyte sedimentation rate (ESR), to possibly elevate DAS28 in FM+ vs. FM- RA patients. METHODS: A PubMed search identified 14 reports which presented comparisons of DAS28-ESR and its four components in RA FM+ vs. FM- groups. Median DAS28, component arithmetic differences, pooled effect sizes and 95% confidence intervals were analysed in the FM+ vs. FM- groups. RESULTS: In FM+ vs. FM- groups, median DAS28 was 5.3 vs. 4.2, SJC 4.0 vs. 3.0, TJC 13.2 vs. 5.3, PATGL 61.6 vs. 39.9, ESR 26.3 vs. 26.5. DAS28-ESR was classified as "high" (>5.1) in 11/14 FM+ groups and "moderate" (3.2-5.1) in all 14 FM- groups. Effect sizes in FM+ vs. FM- groups for DAS28-ESR, SJC, TJC, PATGL, and ESR were large (≥0.8) in 10/14, 1/13, 12/13, 7/13, and 1/13 comparisons, respectively, and pooled effect sizes 0.84 (0.3, 1.4), 0.33 (-0.4, 1.0), 1.27 (0.01, 2.5), 0.91 (-0.6, 2.4), and 0.07 (-0.6, 0.7), respectively. CONCLUSIONS: DAS28-ESR is elevated significantly in FM+ vs. FM- RA patients; pooled effect sizes were highest for TJC, followed by PATGL, SJC and ESR. The findings appear relevant to response and remission criteria, treat-to-target, and general management of RA.

How consistent are the key recommendations, and what is the quality of guidelines and expert consensus regarding paediatric cow's milk protein allergy?

The objective of this study was to assess the quality and consistency of recommendations in clinical practice guidelines (CPGs) and expert consensus on paediatric cow's milk protein allergy (CMPA) to serve as a foundation for future revisions and enhancements of clinical guidelines and consensus documents. We conducted a comprehensive literature search across several databases, including the Chinese Biomedical Literature Database (CBM), PubMed, Embase, Web of Science, UpToDate, ClinicalKey, DynaMed Plus and BMJ Best Practice. We spanned the search period from the inception of each database through October 1, 2023. We integrated subject headings (MeSH/Emtree) and keywords into the search strategy, used the search methodologies of existing literature and developed it in collaboration with a librarian. Two trained researchers independently conducted the literature screening and data extraction. We evaluated methodological quality and recommendations by using the Appraisal of Guidelines for Research & Evaluation II (AGREE II) and AGREE-Recommendations for Excellence (AGREE-REX) tools. Moreover, we compared and summarized key recommendations from high-quality CPGs. Our study included 27 CPGs and expert consensus documents on CMPA. Only four CPGs (14.8%) achieved a high-quality AGREE II rating. The four high-quality CPGs consistently provided recommendations for CMPA. The highest scoring domains for AGREE II were 'scope and purpose' (77 ± 12%) and 'clarity of presentation' (75 ± 22%). The lowest scoring domains were 'stakeholder involvement' (49 ± 21%), 'rigor of development' (34 ± 20%) and 'applicability' (12 ± 20%). Evaluation with AGREE-REX generally demonstrated low scores across its domains.   Conclusion: Recommendations within high-quality CPGs for the paediatric CMPA showed fundamental consistency. Nevertheless, the methodology and recommendation content of CPGs and the expert consensus exhibited low quality, thus indicating a substantial scope for enhancement. Guideline developers should rigorously follow the AGREE II and AGREE-REX standards in creating CPGs or expert consensuses to guarantee their clinical efficacy in managing paediatric CMPA. What is Known: • The quality of clinical practice guidelines and expert consensus on paediatric cow's milk protein allergy (CMPA) remains uncertain. • There is a lack of clarity regarding the consistency of crucial recommendations for CMPA management. What is New: • Improving the methodological quality of guidelines and consensus on CMPA requires greater emphasis on stakeholder engagement, rigorous development processes, and practical applicability. • The recommendations from four high-quality guidelines align. However, addressing clinical applicability, integrating values and preferences, and ensuring actionable implementation are critical to improving the quality of all guidelines.

Artificial intelligence as a prediction tool for orthognathic surgery assessment.

INTRODUCTION: An ideal orthodontic treatment involves qualitative and quantitative measurements of dental and skeletal components to evaluate patients' discrepancies, such as facial, occlusal, and functional characteristics. Deciding between orthodontics and orthognathic surgery remains challenging, especially in borderline patients. Advances in technology are aiding clinical decisions in orthodontics. The increasing availability of data and the era of big data enable the use of artificial intelligence to guide clinicians' diagnoses. This study aims to test the capacity of different machine learning (ML) models to predict whether orthognathic surgery or orthodontics treatment is required, using soft and hard tissue cephalometric values. METHODS: A total of 920 lateral radiographs from patients previously treated with either conventional orthodontics or in combination with orthognathic surgery were used, comprising n = 558 Class II and n = 362 Class III patients, respectively. Thirty-two measures were obtained from each cephalogram at the initial appointment. The subjects were randomly divided into training (n = 552), validation (n = 183), and test (n = 185) datasets, both as an entire sample and divided into Class II and Class III sub-groups. The extracted data were evaluated using 10 machine learning models and by a four-expert panel consisting of orthodontists (n = 2) and surgeons (n = 2). RESULTS: The combined prediction of 10 models showed top-ranked performance in the testing dataset for accuracy, F1-score, and AUC (entire sample: 0.707, 0.706, 0.791; Class II: 0.759, 0.758, 0.824; Class III: 0.822, 0.807, 0.89). CONCLUSIONS: The proposed combined 10 ML approach model accurately predicted the need for orthognathic surgery, showing better performance in Class III patients.

Return to flight duty (RTFD) after posterior lumbar spine surgery for symptomatic lumbar disc herniation (LDH) and lumbar isthmic spondylolisthesis (LIS) in Chinese military pilots.

BACKGROUND: Symptomatic lumbar disc herniation (LDH) and lumbar isthmic spondylolisthesis (LIS) present significant challenges for military pilots, which may result in grounding if not effectively managed. Surgical treatment for LDH and LIS may offer a pathway to return to flight duty (RTFD), but recent data on this crucial topic is lacking. This study seeks to address this gap by investigating the RTFD outcomes among Chinese military pilots who have undergone lumbar spine surgery for symptomatic LDH and LIS. METHODS: A retrospective review was conducted on active-duty military pilots who underwent isolated decompressive or fusion procedures at an authorized military medical center from March 1, 2007, to March 1, 2023. The analysis utilized descriptive statistics to examine demographic, occupational, surgical, and outcome data, with a particular focus on preoperative flight status, recommended clearance by spine surgeons, and actual RTFD outcomes and time. RESULTS: Among the identified cases of active-duty military pilots with LDH or LIS treated by lumbar surgery (n = 24), 70.8% (17 of 24) consistently maintained RTFD status without encountering surgical complications or medical issues during the follow-up period. Of the seven pilots who did not RTFD, one retired within a year of surgery, two had anterior cruciate ligament injuries, three had residual radicular symptoms, and one had chronic low back pain. Excluding pilots who retired and did not RTFD for reasons unrelated to their lumbar conditions, the RTFD rate stood at 81.0% (17 of 21). The median time for recommended clearance by spine surgeons was 143.0 days (inter-quartile range, 116.5-196.0), while the median duration for actual RTFD attainment was 221.0 days (inter-quartile range, 182.0-300.0). The median follow-up post-lumbar surgery was 1.7 years (inter-quartile range, 0.4-2.9). CONCLUSION: Most military pilots diagnosed with symptomatic LDH and LIS can continue their careers and regain active-duty flight status following lumbar spine surgery, as reflected by the high RTFD rate. Lumbar spine surgery can successfully alleviate the physical constraints associated with spinal conditions, facilitating the return of military pilots to their demanding profession.

Comparison for the diagnostic performance of early diagnostic methods for biliary atresia: a systematic review and network meta-analysis.

BACKGROUND: Biliary atresia (BA), a progressive condition affecting canalicular-bile duct function/anatomy, requires prompt surgical intervention for favorable outcomes. Therefore, we conducted a network meta-analysis of common diagnostic methods to assess their performance and provide evidence-based support for clinical decision-making. METHODS: We reviewed literature in PubMed, EMBASE, and Cochrane for BA diagnostics. The search included gamma-glutamyl transferase (GGT), direct/combined bilirubin, matrix metalloproteinase 7 (MMP-7), ultrasonic triangular cord sign (TCS), hepatic scintigraphy (HS), and percutaneous cholangiocholangiography/percutaneous transhepatic cholecysto-cholangiography (PCC/PTCC). QUADAS-2 assessed study quality. Heterogeneity and threshold effect were evaluated using I2 and Spearman's correlation. We combined effect estimates, constructed SROC models, and conducted a network meta-analysis based on the ANOVA model, along with meta-regression and subgroup analysis, to obtain precise diagnostic performance assessments for BA. RESULTS: A total of 40 studies were included in our analysis. GGT demonstrated high diagnostic accuracy for BA with a sensitivity of 81.5% (95% CI 0.792-0.836) and specificity of 72.1% (95% CI 0.693-0.748). Direct bilirubin/conjugated bilirubin showed a sensitivity of 87.6% (95% CI 0.833-0.911) but lower specificity of 59.4% (95% CI 0.549-0.638). MMP-7 exhibited a total sensitivity of 91.5% (95% CI 0.893-0.934) and a specificity of 84.3% (95% CI 0.820-0.863). TCS exhibited a sensitivity of 58.1% (95% CI 0.549-0.613) and high specificity of 92.9% (95% CI 0.911-0.944). HS had a high sensitivity of 98.4% (95% CI 0.968-0.994) and moderate specificity of 79.0% (95% CI 0.762-0.816). PCC/PTCC exhibited excellent diagnostic performance with a sensitivity of 100% (95% CI 0.900-1.000) and specificity of 87.0% (95% CI 0.767-0.939). Based on the ANOVA model, the network meta-analysis revealed that MMP-7 ranked second overall, with PCC/PTCC ranking first, both exhibiting superior diagnostic accuracy compared to other techniques. Our analysis showed no significant bias in most methodologies, but MMP-7 and hepatobiliary scintigraphy exhibited biases, with p values of 0.023 and 0.002, respectively. CONCLUSION: MMP-7 and ultrasound-guided PCC/PTCC show diagnostic potential in the early diagnosis of BA, but their clinical application is restricted due to practical limitations. Currently, the cutoff value of MMP-7 is unclear, and further evidence-based medical research is needed to firmly establish its diagnostic value. Until more evidence is available, MMP-7 is not suitable for widespread diagnostic use. Therefore, considering cost and operational simplicity, liver function tests combined with ultrasound remain the most clinically valuable non-invasive diagnostic methods for BA.

Biliary atresia: the development, pathological features, and classification of the bile duct.

Biliary atresia is an occlusive biliary disease involving intrahepatic and extrahepatic bile ducts. Its etiology and pathogenesis are unclear. There are many manifestations of bile duct involvement in biliary atresia, but little is known about its occurrence and development. In addition, different classification methods have been proposed in different periods of biliary atresia, each with its advantages and disadvantages. The combined application of biliary atresia classification will help to improve the survival rate of patients with native liver. Therefore, this article reviews the development, pathological features, and classification of intrahepatic and extrahepatic bile ducts in biliary atresia, to provide a reference for the study of the pathogenesis and the choice of treatment methods.

Unraveling the Ultrafast Coherent Dynamics of Exciton Polariton Propagation at Room Temperature.

Exciton polaritons are widely considered as promising platforms for developing room-temperature polaritonic devices, owing to the high-speed propagation and nonlinear interactions. However, it remains challenging to explore the dynamics of exciton polaritons specifically at room temperature, where the lifetime could be as small as a few picoseconds and the prevailing time-averaged measurement cannot give access to the true nature of it. Herein, by using the time-resolved photoluminescence, we have successfully traced the ultrafast coherent dynamics of a moving exciton polariton condensate in a one-dimensional perovskite microcavity. The propagation speed is directly measured to be ∼12.2 ± 0.8 µm/ps. Moreover, we have developed a time-resolved Michelson interferometry to quantify the time-dependent phase coherence, which reveals that the actual coherence time of exciton polaritons could be much longer (nearly 100%) than what was believed before. Our work sheds new light on the ultrafast coherent propagation of exciton polaritons at room temperature.

End Group Nonplanarization Enhances Phototherapy Efficacy of A-D-A Fused-Ring Photosensitizer for Tumor Phototherapy.

Enhancing the phototherapy efficacy of organic photosensitizers through molecular design is a fascinating but challenging task. Herein, we propose a simple design strategy to first realize the generation of superoxide anion radical (O2•-) by A-D-A fused-ring photosensitizers. Through replacing one cyano group of traditional end group with an ester group, we designed a novel nonplanar end group (A unit) to synthesize a novel A-D-A photosensitizer F8CA. In a comparison with its counterpart F8CN with the traditional end group, F8CA displays more loose packing and larger spin-orbit coupling constants. The F8CA nanoparticles showed higher photodynamic activities with the generation capability of singlet oxygen (1O2), hydroxyl radical (•OH), and O2•-, while F8CN nanoparticles could only generate 1O2 and •OH. In addition, F8CA nanoparticles still remain high photothermal conversion efficiency (61%). As a result, F8CA nanoparticles perform well in hypoxia-tolerant tumor phototherapy. This study brings an effective design thought for A-D-A photosensitizers.

Bayesian sparse heritability analysis with high-dimensional neuroimaging phenotypes.

Heritability analysis plays a central role in quantitative genetics to describe genetic contribution to human complex traits and prioritize downstream analyses under large-scale phenotypes. Existing works largely focus on modeling single phenotype and currently available multivariate phenotypic methods often suffer from scaling and interpretation. In this article, motivated by understanding how genetic underpinning impacts human brain variation, we develop an integrative Bayesian heritability analysis to jointly estimate heritabilities for high-dimensional neuroimaging traits. To induce sparsity and incorporate brain anatomical configuration, we impose hierarchical selection among both regional and local measurements based on brain structural network and voxel dependence. We also use a nonparametric Dirichlet process mixture model to realize grouping among single nucleotide polymorphism-associated phenotypic variations, providing biological plausibility. Through extensive simulations, we show the proposed method outperforms existing ones in heritability estimation and heritable traits selection under various scenarios. We finally apply the method to two large-scale imaging genetics datasets: the Alzheimer's Disease Neuroimaging Initiative and United Kingdom Biobank and show biologically meaningful results.