Meta-analysis of machine learning models for the diagnosis of central precocious puberty based on clinical, hormonal (laboratory) and imaging data.

Background: Central precocious puberty (CPP) is a common endocrine disorder in children, and its diagnosis primarily relies on the gonadotropin-releasing hormone (GnRH) stimulation test, which is expensive and time-consuming. With the widespread application of artificial intelligence in medicine, some studies have utilized clinical, hormonal (laboratory) and imaging data-based machine learning (ML) models to identify CPP. However, the results of these studies varied widely and were challenging to directly compare, mainly due to diverse ML methods. Therefore, the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for CPP remains elusive. The aim of this study was to investigate the diagnostic value of ML models based on clinical, hormonal (laboratory) and imaging data for CPP through a meta-analysis of existing studies. Methods: We conducted a comprehensive search for relevant English articles on clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP, covering the period from the database creation date to December 2023. Pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve, and area under the curve (AUC) were calculated to assess the diagnostic value of clinical, hormonal (laboratory) and imaging data-based ML models for diagnosing CPP. The I2 test was employed to evaluate heterogeneity, and the source of heterogeneity was investigated through meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. Results: Six studies met the eligibility criteria. The pooled sensitivity and specificity were 0.82 (95% confidence interval (CI) 0.62-0.93) and 0.85 (95% CI 0.80-0.90), respectively. The LR+ was 6.00, and the LR- was 0.21, indicating that clinical, hormonal (laboratory) and imaging data-based ML models exhibited an excellent ability to confirm or exclude CPP. Additionally, the SROC curve showed that the AUC of the clinical, hormonal (laboratory) and imaging data-based ML models in the diagnosis of CPP was 0.90 (95% CI 0.87-0.92), demonstrating good diagnostic value for CPP. Conclusion: Based on the outcomes of our meta-analysis, clinical and imaging data-based ML models are excellent diagnostic tools with high sensitivity, specificity, and AUC in the diagnosis of CPP. Despite the geographical limitations of the study findings, future research endeavors will strive to address these issues to enhance their applicability and reliability, providing more precise guidance for the differentiation and treatment of CPP.

Subregional thalamic functional connectivity abnormalities and cognitive impairments in first-episode schizophrenia.

BACKGROUND: Previous studies have documented thalamic functional connectivity (FC) abnormalities in schizophrenia, typically examining the thalamus as a whole. The specific link between subregional thalamic FC and cognitive deficits in first-episode schizophrenia (FES) remains unexplored. METHODS: Using data from resting-state functional magnetic resonance imaging, we compared whole-brain FC with thalamic subregions between patients and HCs, and analyzed FC changes in drug-naïve patients separately. We then examined correlations between FC abnormalities with both cognitive impairment and clinical symptoms. RESULTS: A total of 33 FES patients (20 drug-naïve) and 32 age- and sex-matched healthy controls (HCs) were included. Compared to HCs, FES patients exhibited increased FC between specific thalamic subregions and cortical regions, particularly bilateral middle temporal lobe and cuneus gyrus, left medial superior frontal gyrus, and right inferior/superior occipital gyrus. Decreased FC was observed between certain thalamic subregions and the left inferior frontal triangle. These findings were largely consistent in drug-naïve patients. Notably, deficits in social cognition and visual learning in FES patients correlated with increased FC between certain thalamic subregions and cortical regions involving the right superior occipital gyrus and cuneus gyrus. The severity of negative symptoms was associated with increased FC between a thalamic subregion and the left middle temporal gyrus. CONCLUSION: Our findings suggest FC abnormalities between thalamic subregions and cortical areas in FES patients. Increased FC correlated with cognitive deficits and negative symptoms, highlighting the importance of thalamo-cortical connectivity in the pathophysiology of schizophrenia.

Structural or/and functional MRI-based machine learning techniques for attention-deficit/hyperactivity disorder diagnosis: A systematic review and meta-analysis.

BACKGROUND: The aim of this study was to investigate the diagnostic value of ML techniques based on sMRI or/and fMRI for ADHD. METHODS: We conducted a comprehensive search (from database creation date to March 2024) for relevant English articles on sMRI or/and fMRI-based ML techniques for diagnosing ADHD. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), summary receiver operating characteristic (SROC) curve and area under the curve (AUC) were calculated to assess the diagnostic value of sMRI or/and fMRI-based ML techniques. The I2 test was used to assess heterogeneity and the source of heterogeneity was investigated by performing a meta-regression analysis. Publication bias was assessed using the Deeks funnel plot asymmetry test. RESULTS: Forty-three studies were included in the systematic review, 27 of which were included in our meta-analysis. The pooled sensitivity and specificity of sMRI or/and fMRI-based ML techniques for the diagnosis of ADHD were 0.74 (95 % CI 0.65-0.81) and 0.75 (95 % CI 0.67-0.81), respectively. SROC curve showed that AUC was 0.81 (95 % CI 0.77-0.84). Based on these findings, the sMRI or/and fMRI-based ML techniques have relatively good diagnostic value for ADHD. LIMITATIONS: Our meta-analysis specifically focused on ML techniques based on sMRI or/and fMRI studies. Since EEG-based ML techniques are also used for diagnosing ADHD, further systematic analyses are necessary to explore ML methods based on multimodal medical data. CONCLUSION: sMRI or/and fMRI-based ML technique is a promising objective diagnostic method for ADHD.

Adaptive functions of structural variants in human brain development.

Quantifying the structural variants (SVs) in nonhuman primates could provide a niche to clarify the genetic backgrounds underlying human-specific traits, but such resource is largely lacking. Here, we report an accurate SV map in a population of 562 rhesus macaques, verified by in-house benchmarks of eight macaque genomes with long-read sequencing and another one with genome assembly. This map indicates stronger selective constrains on inversions at regulatory regions, suggesting a strategy for prioritizing them with the most important functions. Accordingly, we identified 75 human-specific inversions and prioritized them. The top-ranked inversions have substantially shaped the human transcriptome, through their dual effects of reconfiguring the ancestral genomic architecture and introducing regional mutation hotspots at the inverted regions. As a proof of concept, we linked APCDD1, located on one of these inversions and down-regulated specifically in humans, to neuronal maturation and cognitive ability. We thus highlight inversions in shaping the human uniqueness in brain development.

Selective activation of IFNγ-ipilimumab enhances the therapeutic effect and safety of ipilimumab.

INTRODUCTION: Immune checkpoint inhibitor therapy is a highly promising strategy for clinical treatment of cancer. Among these inhibitors, ipilimumab stands out for its ability to induce cytotoxic T cell proliferation and activation by binding to CTLA-4. However, ipilimumab also gives rise to systemic immune-related adverse effects and tumor immune evasion, limiting its effectiveness. OBJECTIVES: We developed IFNγ-ipilimumab and confirmed that the addition of INF-γ does not alter the fundamental properties of ipilimumab. RESULTS: IFNγ-ipilimumab can be activated by matrix metalloproteinases, thereby promoting the IFNγ signaling pathway and enhancing the cytotoxicity of T cells. In vivo studies demonstrated that IFNγ-ipilimumab enhances the therapeutic effect of ipilimumab against colorectal cancer by increasing CD8+ and CD4+ lymphocyte infiltration into the tumor area and inducing MHC-I expression in tumor cells. Mice treated with IFNγ-ipilimumab showed higher survival rates and body weight, as well as lower CD4+ and CD8+ lymphocyte activation rates in the blood and reduced organ damage. CONCLUSION: IFNγ-ipilimumab improved the effectiveness of ipilimumab while reducing its side effects. It is likely that future immunotherapies would rely on such antibodies to activate local cancer cells or immune cells, thereby increasing the therapeutic effectiveness of cancer treatments and ensuring their safety.

Exploring the therapeutic potential of DV-B-120 as an inhibitor of dengue virus infection.

Dengue fever, an infectious disease prevalent in subtropical and tropical regions, currently lacks effective small-molecule drugs as treatment. In this study, we used a fluorescence peptide cleavage assay to screen seven compounds to assess their inhibition of the dengue virus (DENV) NS2B-NS3 protease. DV-B-120 demonstrated superior inhibition of NS2B-NS3 protease activity and lower toxicity compared to ARDP0006. The selectivity index of DV-B-120 was higher than that of ARDP0006. In vivo assessments of the antiviral efficacy of DV-B-120 against DENV replication demonstrated delayed mortality of suckling mice treated with the compound, with 60-80% protection against life-threatening effects, compared to the outcomes of DENV-infected mice treated with saline. The lower clinical scores of DENV-infected mice treated with DV-B-120 indicated a reduction in acute-progressive illness symptoms, underscoring the potential therapeutic impact of DV-B-120. Investigations of DV-B-120's ability to restore the antiviral type I IFN response in the brain tissue of DENV-infected ICR suckling mice demonstrated its capacity to stimulate IFN and antiviral IFN-stimulated gene expression. DV-B-120 not only significantly delayed DENV-2-induced mortality and illness symptoms but also reduced viral numbers in the brain, ultimately restoring the innate antiviral response. These findings strongly suggest that DV-B-120 holds promise as a therapeutic agent against DENV infection and highlight its potential contribution in addressing the current lack of effective treatments for this infectious disease.IMPORTANCEThe prevalence of dengue virus (DENV) infection in tropical and subtropical regions is escalating due to factors like climate change and mosquito vector expansion. With over 300 million annual infections and potentially fatal outcomes, the urgent need for effective treatments is evident. While the approved Dengvaxia vaccine has variable efficacy, there are currently no antiviral drugs for DENV. This study explores seven compounds targeting the NS2B-NS3 protease, a crucial protein in DENV replication. These compounds exhibit inhibitory effects on DENV-2 NS2B-NS3, holding promise for disrupting viral replication and preventing severe manifestations. However, further research, including animal testing, is imperative to assess therapeutic efficacy and potential toxicity. Developing safe and potent treatments for DENV infection is critical in addressing the rising global health threat posed by this virus.

Extracellular vesicles and cancer stemness in hepatocellular carcinoma - is there a link?

Hepatocellular carcinoma (HCC) is a highly aggressive malignancy, with high recurrence rates and notorious resistance to conventional chemotherapy. Cancer stemness refers to the stem-cell-like phenotype of cancer cells and has been recognized to play important roles in different aspects of hepatocarcinogenesis. Small extracellular vesicles (sEVs) are small membranous particles secreted by cells that can transfer bioactive molecules, such as nucleic acids, proteins, lipids, and metabolites, to neighboring or distant cells. Recent studies have highlighted the role of sEVs in modulating different aspects of the cancer stemness properties of HCC. Furthermore, sEVs derived from diverse cellular sources, such as cancer cells, stromal cells, and immune cells, contribute to the maintenance of the cancer stemness phenotype in HCC. Through cargo transfer, specific signaling pathways are activated within the recipient cells, thus promoting the stemness properties. Additionally, sEVs can govern the secretion of growth factors from non-cancer cells to further maintain their stemness features. Clinically, plasma sEVs may hold promise as potential biomarkers for HCC diagnosis and treatment prediction. Understanding the underlying mechanisms by which sEVs promote cancer stemness in HCC is crucial, as targeting sEV-mediated communication may offer novel strategies in treatment and improve patient outcome.

A toroidal SAW gyroscope with focused IDTs for sensitivity enhancement.

A surface acoustic wave (SAW) gyroscope measures the rate of rotational angular velocity by exploiting a phenomenon known as the SAW gyroscope effect. Such a gyroscope is a great candidate for application in harsh environments because of the simplification of the suspension vibration mechanism necessary for traditional microelectromechanical system (MEMS) gyroscopes. Here, for the first time, we propose a novel toroidal standing-wave-mode SAW gyroscope using focused interdigitated transducers (FIDTs). Unlike traditional SAW gyroscopes that use linear IDTs to generate surface acoustic waves, which cause beam deflection and result in energy dissipation, this study uses FIDTs to concentrate the SAW energy based on structural features, resulting in better focusing performance and increased SAW amplitude. The experimental results reveal that the sensitivity of the structure is 1.51 µV/(°/s), and the bias instability is 0.77°/s, which are improved by an order of magnitude compared to those of a traditional SAW gyroscope. Thus, the FIDT component can enhance the performance of the SAW gyroscope, demonstrating its superiority for angular velocity measurements. This work provides new insights into improving the sensitivity and performance of SAW gyroscopes.

Premature coronary heart disease complicated with hypertension in hospitalized patients: Incidence, risk factors, cardiovascular-related comorbidities and prognosis, 2008-2018.

Background: The clinical characteristics and risk factors of all-cause mortality in young hospitalized patients with comorbid coronary heart disease and hypertension (CAD + HT) are not well-characterized. Method: A total of 2288 hospitalized CAD patients (age<45 years) with or without hypertension in the Chinese PLA General Hospital from August 5, 2008 to June 22, 2018 were conducted. The risk factors of all-cause mortality were estimated in young CAD + HT patients by COX models. Results: The overall prevalence of hypertension in young CAD patients was 50.83% (n = 1163). CAD + HT patients had older age, higher heart rate, BMI, uric acid, triglyceride and lower level of eGFR and HDL-C than CAD patients (P < 0.05). The proportion of cardiovascular-related comorbidities (including obesity, diabetes mellitus, hyperuricemia and chronic kidney disease [CKD]) in the CAD + HT group was significantly higher than that in CAD group (P < 0.0001). The risk of all-cause mortality was higher in CAD + HT patients, although after adjusting for all covariates, there was no significant difference between the two groups. Furthermore, CKD (HR, 3.662; 95% CI, 1.545-8.682) and heart failure (HF) (HR, 3.136; 95%CI, 1.276-7.703) were associated with an increased risk of all-cause mortality and RAASi (HR, 0.378; 95%CI, 0.174-0.819) had a beneficial impact in CAD + HT patients. Conclusions: Hypertension was highly prevalent in young CAD patients. Young CAD + HT patients had more cardiovascular metabolic risk factors, more cardiovascular-related comorbidities and higher risk of all-cause mortality. CKD and HF were the risk factors, while RAASi was a protective factor, of all-cause mortality in CAD + HT patients.

Assessment of TUFT1 and Rac1-GTP levels in triple-negative breast cancer patients: clinical and pathological correlations.

OBJECTIVE: The primary goal of this study was to investigate the expressions of TUFT1 (Tuftelin) and Rac1-GTP in the cancerous tissues of individuals with triple-negative breast cancer (TNBC). Additionally, we aimed to explore the correlation between TUFT1 and Rac1-GTP expressions and examine the associations of TUFT1 and Rac1-GTP expressions with the clinical and pathological indicators of the patients. METHODS: Ninety-six patients diagnosed with TNBC, scheduled for surgery between May 2022 and November 2022, were enrolled in this study. Cancerous tissue specimens were collected from these patients, and immunohistochemistry was employed to evaluate the levels of TUFT1 and Rac1-GTP expressions in the cancerous tissues. Subsequent to data collection, a comprehensive analysis was conducted to examine the correlation between TUFT1 and Rac1-GTP expressions. Furthermore, we sought to assess the associations of TUFT1 and Rac1-GTP expressions with the clinical and pathological indicators of the patients. RESULTS: The TUFT1 protein was expressed in both the membrane and cytoplasm of TNBC cancer cells, with notably higher expression observed in the cytoplasm. Rac1-GTP was primarily expressed in the cytoplasm. There was a positive correlation between the levels of TUFT1 and Rac1-GTP expressions (χ2 = 9.816, P < 0.05). The levels of TUFT1 and Rac1-GTP protein expressions showed no correlation with patient age (χ2 = 2.590, 2.565, P > 0.05); however, they demonstrated a positive correlation with tumor size (χ2 = 5.592,5.118), histological grading (χ2 = 6.730, 5.443), and lymph node metastasis (χ2 = 8.221, 5.180) (all with a significance level of P < 0.05). CONCLUSION: A significant correlation was identified between the levels of TUFT1 and Rac1-GTP expressions in the cancerous tissues of patients with TNBC, suggesting a close association with the progression of TNBC. The two molecules play significant roles in facilitating an early diagnosis and treatment of TNBC.

Comprehensive proteomics of CSF, plasma, and urine identify DDC and other biomarkers of early Parkinson's disease.

Parkinson's disease (PD) starts at the molecular and cellular level long before motor symptoms appear, yet there are no early-stage molecular biomarkers for diagnosis, prognosis prediction, or monitoring therapeutic response. This lack of biomarkers greatly impedes patient care and translational research-L-DOPA remains the standard of care more than 50 years after its introduction. Here, we performed a large-scale, multi-tissue, and multi-platform proteomics study to identify new biomarkers for early diagnosis and disease monitoring in PD. We analyzed 4877 cerebrospinal fluid, blood plasma, and urine samples from participants across seven cohorts using three orthogonal proteomics methods: Olink proximity extension assay, SomaScan aptamer precipitation assay, and liquid chromatography-mass spectrometry proteomics. We discovered that hundreds of proteins were upregulated in the CSF, blood, or urine of PD patients, prodromal PD patients with DAT deficit and REM sleep behavior disorder or anosmia, and non-manifesting genetic carriers of LRRK2 and GBA mutations. We nominate multiple novel hits across our analyses as promising markers of early PD, including DOPA decarboxylase (DDC), also known as L-aromatic acid decarboxylase (AADC), sulfatase-modifying factor 1 (SUMF1), dipeptidyl peptidase 2/7 (DPP7), glutamyl aminopeptidase (ENPEP), WAP four-disulfide core domain 2 (WFDC2), and others. DDC, which catalyzes the final step in dopamine synthesis, particularly stands out as a novel hit with a compelling mechanistic link to PD pathogenesis. DDC is consistently upregulated in the CSF and urine of treatment-naïve PD, prodromal PD, and GBA or LRRK2 carrier participants by all three proteomics methods. We show that CSF DDC levels correlate with clinical symptom severity in treatment-naïve PD patients and can be used to accurately diagnose PD and prodromal PD. This suggests that urine and CSF DDC could be a promising diagnostic and prognostic marker with utility in both clinical care and translational research.

Identifying Predictors for Hypoplastic Aortic Arch (HAA) in Pediatric Patients with Complex Coarctation of the Aorta (CoA).

OBJECTIVE: HAA is a significant risk factor in complex CoA patients. We conducted a retrospective study to explore the relationship between HAA and other cardiovascular factors. METHODS: We analyzed 103 patients diagnosed with complex CoA using CT angiography and echocardiography. Aortic diameter was measured at six levels, and severe coarctation was defined as coarctation site to diaphragmatic level ratio (CDR) < 50%. Correlations between non-HAA and HAA groups were assessed. Univariate and multivariate logistic regression identified HAA risk factors. RESULTS: Among 103 children with complex CoA, 55 were in the non-HAA group and 48 in the HAA group. The incidence of PDA (56.3% vs. 32.7%, p < 0.05), severe coarctation (CDR < 50%, 81.3% vs. 34.5%, p < 0.01), and collateral arteries (39.6% vs. 0, p < 0.01) were higher in the HAA group than one in the non-HAA group. The aortic arch size was positively correlated with age and negatively correlated with severe coarctation, VSD, collateral arteries, and left heart dysfunction. Logistic regression results showed that collateral arteries were risk factors for the whole aortic arch (proximal arch OR = 11.458; p < 0.01, distal arch OR = 4.211; p < 0.05, and isthmus OR = 11.744; p < 0.01), severe coarctation (OR = 6.653; p < 0.01), and left heart dysfunction (OR = 5.149; p < 0.01) associated with isthmus hypoplasia. CONCLUSION: This study highlights the prevalence of HAA in complex CoA patients and its associations with various cardiovascular factors. These insights improve diagnosis and treatment approaches.

Adjusting Incidence Estimates with Laboratory Test Performances: A Pragmatic Maximum Likelihood Estimation-Based Approach.

Understanding the incidence of disease is often crucial for public policy decision-making, as observed during the COVID-19 pandemic. Estimating incidence is challenging, however, when the definition of incidence relies on tests that imperfectly measure disease, as in the case when assays with variable performance are used to detect the SARS-CoV-2 virus. To our knowledge, there are no pragmatic methods to address the bias introduced by the performance of labs in testing for the virus. In the setting of a longitudinal study, we developed a maximum likelihood estimation-based approach to estimate laboratory performance-adjusted incidence using the expectation-maximization algorithm. We constructed confidence intervals (CIs) using both bootstrapped-based and large-sample interval estimator approaches. We evaluated our methods through extensive simulation and applied them to a real-world study (TrackCOVID), where the primary goal was to determine the incidence of and risk factors for SARS-CoV-2 infection in the San Francisco Bay Area from July 2020 to March 2021. Our simulations demonstrated that our method converged rapidly with accurate estimates under a variety of scenarios. Bootstrapped-based CIs were comparable to the large-sample estimator CIs with a reasonable number of incident cases, shown via a simulation scenario based on the real TrackCOVID study. In more extreme simulated scenarios, the coverage of large-sample interval estimation outperformed the bootstrapped-based approach. Results from the application to the TrackCOVID study suggested that assuming perfect laboratory test performance can lead to an inaccurate inference of the incidence. Our flexible, pragmatic method can be extended to a variety of disease and study settings.

Association of differential censoring with survival and suboptimal control arms among oncology clinical trials.

Differential censoring (DC), referring to censoring imbalance between treatment arms, may bias the interpretation of survival outcomes in clinical trials. In 146 phase 3 oncology trials with statistically significant time-to-event surrogate primary endpoints (PEPs), we evaluated the association between DC in the surrogate PEP, control arm adequacy, and the subsequent statistical significance of OS results. Twenty-four (16%) trials exhibited DC favoring the control arm (ConDC), while 15 (10%) exhibited experimental arm DC (ExpDC). Positive OS was more common in ConDC trials (63%) than trials without DC (37%) or with ExpDC (47%; odds ratio [OR] 2.64, 95% CI 1.10-7.20; P=.04). ConDC trials more frequently used suboptimal control arms (46%) compared to 20% without DC and 13% with ExpDC (OR 3.60, 95% CI 1.29-10.0; P=.007). The presence of ConDC in trials with surrogate PEPs, especially in those with OS conversion, may indicate an inadequate control arm and should be examined and explained.

Individualized prediction of cognitive test scores from functional brain connectome in patients with first-episode late-life depression.

BACKGROUND: In the realm of cognitive screening, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) are widely utilized for detecting cognitive deficits in patients with late-life depression (LLD), However, the interindividual variability in neuroimaging biomarkers contributing to individual-specific symptom severity remains poorly understood. In this study, we used a connectome-based predictive model (CPM) approach on resting-state functional magnetic resonance imaging data from patients with LLD to establish individualized prediction models for the MoCA and the MMSE scores. METHODS: We recruited 135 individuals diagnosed with first-episode LLD for this research. Participants underwent the MMSE and MoCA tests, along with resting-state functional magnetic resonance imaging scans. Functional connectivity matrices derived from these scans were utilized in CPM models to predict MMSE or MoCA scores. Predictive precision was assessed by correlating predicted and observed scores, with the significance of prediction performance evaluated through a permutation test. RESULTS: The negative model of the CPM procedure demonstrated a significant capacity to predict MoCA scores (r = -0.309, p = 0.002). Similarly, the CPM procedure could predict MMSE scores (r = -0.236, p = 0.016). The predictive models for cognitive test scores in LLD primarily involved the visual network, somatomotor network, dorsal attention network, and ventral attention network. CONCLUSIONS: Brain functional connectivity emerges as a promising predictor of personalized cognitive test scores in LLD, suggesting that functional connectomes are potential neurobiological markers for cognitive performance in patients with LLD.

Dark and Dronc activation in Drosophila melanogaster.

The onset of apoptosis is characterized by a cascade of caspase activation, where initiator caspases are activated by a multimeric adaptor complex known as the apoptosome. In Drosophila melanogaster, the initiator caspase Dronc undergoes autocatalytic activation in the presence of the Dark apoptosome. Despite rigorous investigations, the activation mechanism for Dronc remains elusive. Here, we report the cryo-EM structures of an auto-inhibited Dark monomer and a single-layered, multimeric Dark/Dronc complex. Our biochemical analysis suggests that the auto-inhibited Dark oligomerizes upon binding to Dronc, which is sufficient for the activation of both Dark and Dronc. In contrast, the previously observed double-ring Dark apoptosome may represent a non-functional or "off-pathway" conformation. These findings expand our understanding on the molecular mechanism of apoptosis in Drosophila.

Fine-tuning of thermally induced SCO behaviors of trinuclear cyanido-bridged complexes by regulating the electron donating ability of CCN-terminal fragments.

To achieve fine regulation of FeII SCO behavior, a series of trinuclear cyanido-bridged complexes trans-[CpMen(dppe)MII(CN)]2[Fe1II(abpt)2](OTf)2 (1-4) (1, M = Fe2 and n = 1; 2, M = Fe2 and n = 4; 3, M = Fe2 and n = 5; 4, M = Ru and n = 5; CpMen = alkyl cyclopentadienyl with n = 1, 4, 5; dppe = 1,2-bis-(diphenylphosphino)ethane; abpt = 4-amino-3,5-bis-(pyridin-2-yl)-1,2,4-triazole and OTf = CF3SO3-) were synthesized and fully characterized by using elemental analysis, X-ray crystallography, magnetic measurements, variable-temperature IR spectroscopy and Mössbauer spectroscopy. It is worth mentioning that different from many mononuclear Fe(abpt)2X2 (X = NCS, NCSe, N(CN)2, C(CN)3, (NC)2CC(OCH3)C(CN)2, (NC)2CC(OC2H5)C(CN)2, C16SO3 and Cl) complexes with more than one polymorph, only one polycrystalline form was found in complexes 1-4. Moreover, the thermally induced SCO behaviors of these four complexes are independent of intermolecular π-π interactions. The electron-donating ability of the CCN-terminal fragment of CpMen(dppe)MIICN can be flexibly regulated by changing the methyl number (n) of the cyclopentadiene ligand or metal ion type (MII). These investigations indicate that the electron-donating ability of the CCN-terminal fragment has an influence on the SCO behavior of Fe1II. The spin transition temperature (T1/2) of the complexes decreases with the increase of the electron-donating ability of the fragment CpMen(dppe)MII. This study provides a new strategy to predict and precisely regulate the behaviors of SCO complexes.

Global metabolomics revealed deviations from the metabolic aging clock in colorectal cancer patients.

Background: Markers of aging hold promise in the context of colorectal cancer (CRC) care. Utilizing high-resolution metabolomic profiling, we can unveil distinctive age-related patterns that have the potential to predict early CRC development. Our study aims to unearth a panel of aging markers and delve into the metabolomic alterations associated with aging and CRC. Methods: We assembled a serum cohort comprising 5,649 individuals, consisting of 3,002 healthy volunteers, 715 patients diagnosed with colorectal advanced precancerous lesions (APL), and 1,932 CRC patients, to perform a comprehensive metabolomic analysis. Results: We successfully identified unique age-associated patterns across 42 metabolic pathways. Moreover, we established a metabolic aging clock, comprising 9 key metabolites, using an elastic net regularized regression model that accurately estimates chronological age. Notably, we observed significant chronological disparities among the healthy population, APL patients, and CRC patients. By combining the analysis of circulative carcinoembryonic antigen levels with the categorization of individuals into the "hypo" metabolic aging subgroup, our blood test demonstrates the ability to detect APL and CRC with positive predictive values of 68.4% (64.3%, 72.2%) and 21.4% (17.8%, 25.9%), respectively. Conclusions: This innovative approach utilizing our metabolic aging clock holds significant promise for accurately assessing biological age and enhancing our capacity to detect APL and CRC.

A rank-based approach to evaluate a surrogate marker in a small sample setting.

In clinical studies of chronic diseases, the effectiveness of an intervention is often assessed using "high cost" outcomes that require long-term patient follow-up and/or are invasive to obtain. While much progress has been made in the development of statistical methods to identify surrogate markers, that is, measurements that could replace such costly outcomes, they are generally not applicable to studies with a small sample size. These methods either rely on nonparametric smoothing which requires a relatively large sample size or rely on strict model assumptions that are unlikely to hold in practice and empirically difficult to verify with a small sample size. In this paper, we develop a novel rank-based nonparametric approach to evaluate a surrogate marker in a small sample size setting. The method developed in this paper is motivated by a small study of children with nonalcoholic fatty liver disease (NAFLD), a diagnosis for a range of liver conditions in individuals without significant history of alcohol intake. Specifically, we examine whether change in alanine aminotransferase (ALT; measured in blood) is a surrogate marker for change in NAFLD activity score (obtained by biopsy) in a trial, which compared Vitamin E ($n=50$) versus placebo ($n=46$) among children with NAFLD.

Syntheses, crystal structures and MMCT properties of diruthenium-based cyanido-bridged RuV/VI2-NC-RuII complexes.

The goal of this study was to investigate how the electron-donating capability around the lower valent metal ion and the electron-accepting capability of the higher valent metal ion influence metal to metal charge transfer (MMCT) properties in mixed-valence complexes. A series of trinuclear ruthenium complexes represented as [Ru2(ap-4-Me)3(CH3COO)NCRuCpMex(dppe)][PF6] (CpMex = polymethylcyclopentadienyl, x = 0, 1, and 5; and dppe = 1, 2-bis(diphenylphosphino)ethane, ap-4-Me = 2-anilino-4-methylpyridine) and their one-electron oxidized products were synthesized and fully characterized. The UV-vis-NIR spectra confirmed that as the electron donor character of the CpMex(dppe)RuCN fragment enhanced or the electron-accepting capability of the higher valent diruthenium cluster increased, the RuII → RuV2 or RuVI2 Ru2 MMCT bands shifted to lower energies, which was supported by TDDFT calculations.