Index Plots Research Articles

Geochemical evidences linking the Lower Cretaceous source rocks to the biodegraded bitumen seeps and tar sands in the Gulf of Guinea Basin

The source of biodegraded bitumen seeps and tar sands in the Nigerian axis of the Gulf of Guinea province has been a contentious issue for decades. The most prevalent opinion is that the biodegraded bitumen seeps are migration oils that were degraded by bacterial. In the present study, outcrop source rocks (Lower Cretaceous), core samples (Upper Cretaceous) from a shallow well-x, and bitumen seeps and tar sands from the eastern axis of the Dahomey Basin of Nigeria were analyzed. Rock-Eval™ pyrolysis show that the outcrop rocks are classified as having excellent-very good source quality; in contrast, those from well-x are classified as having only poor-fair quality. The cross plot of hydrogen index (HI) against Tmax indicates that samples from the outcrops contain type II/III organic matter, whereas well samples contain type III organic matter and all source rocks are thermally immature, which is supported by vitrinite reflectance (Ro: 0.20–0.48 %), and biomarker maturity parameters (C32 (S/S + R), MPI-I). In the bitumen seeps and tar sands, isoprenoids, n-alkanes, steranes and hopanes have been degraded, and tricyclic and tetracyclic terpanes are still mostly intact. In addition, C30 hopane and homohopanes have been demethylated, and C25 norhopanes are present in abundance, suggesting that the bitumen seeps and tar sands experienced heavy biodegradation in the range of PM-6 or greater. The distribution of 4,9-DMD, 4,8-DMD and 3,4-DMD diamondoids and the δ13C of saturate and aromatic fractions indicate that the bitumen seeps and tar sands were generated from Types II and III source rocks. The ratio of demethylated Ts/Tm indicates that the samples are low maturity and were generated from immature source rocks. Cross plots of tricyclic terpane ratios (C25/C26TT vs C25TT/C24TeT, C23/C21TT vs (C19+20)/C23TT, and C24TeT/C24TeT + C26TT vs (C19+20)/C23TT) also reveal that the biodegraded bitumen seeps and tar sands are closely related to source rocks in outcrop groups 1 and 2. This conclusion is supported by the ternary plots of tricyclic terpanes, 4,9DMD, 4,8DMD and 3,4DMD diamondoids, and the cross plot of EAI against DMDI-1. The occurrence of exsudatinite in the outcrop source rocks in group 1, consistent with early hydrocarbon generation, and the low ratio of demethylated Ts/Tm (<1) in the bitumen samples confirms that the biodegraded bitumen seeps and tar sands in the Nigerian Dahomey Basin were generated by the Lower Cretaceous source rocks in group 1. The study advances on the previous propositions on the source of bitumen seeps and tar sands and contributes our knowledge in the Gulf of Guinea Basin.

The impact of hepatitis B surface antigen seroconversion on the durability of functional cure induced by pegylated interferon alpha treatment

BackgroundHepatitis B surface antigen (HBsAg) loss is regarded as a pivotal criterion for assessing functional cure in patients diagnosed chronic hepatitis B (CHB). We conducted the research to investigate the real-world performance of HBsAg seroconversion in sustaining HBsAg loss.MethodsThis retrospective analysis confirmed 295 patients who attained HBsAg loss through combination therapy involving nucleos(t)ide analogues (NAs) and pegylated interferon alpha (peg-IFNα). Employing Kaplan–Meier estimates method to conduct survival analysis. The forest plot was used to visualize the results of multivariate Cox regression, and selected variables were included in the nomogram.ResultsHBsAg seroreversion was observed in 45 patients during follow-up periods, with a lower recurrence risk in patients with HBsAg seroconversion at the end of peg-IFNα therapy (EOT) (10.3% vs 37.3% at 96-week, P < 0.0001). Moreover, the sustainability of hepatitis B surface antibody (anti-HBs) in participants continuing therapy after HBsAg seroconversion was superior to those discontinued prematurely (72.5% vs 54.5% at 96 weeks, P = 0.012). Additionally, the former group was also relatively less likely to experience HBsAg reversion during long-term observation (8.4% vs 14.3% at 96 weeks, P = 0.280). Hepatitis B envelope antigen (HBeAg) status, anti-HBs status and consolidation treatment screened by multivariable analysis were utilized to construct a predictive model for HBsAg reversion. The concordance index(C-index = 0.77) and calibration plots indicated satisfactory discrimination and consistency of nomogram.ConclusionsHBsAg seroconversion was beneficial for sustaining functional cure in patients treated with peg-IFNα. Continuing consolidation therapy after HBsAg seroconversion also contributed to maintain HBsAg seroconversion and improve the durability of HBsAg loss. The nomogram illustrated its efficacy as a valuable instrument in showcasing survival probability of functional cure.

Inhibition of Epithelial-Mesenchymal Transition and Migration in Cisplatin-resistant Cancer Through Combined Treatment With Cisplatin and SH003.

This study investigated the synergistic effects of combining cisplatin and SH003 treatment on the viability, apoptosis, cytotoxicity, migration and epithelial-mesenchymal transition (EMT) in cisplatin-resistant cancer cell lines YD-8/CIS, YD-9/CIS and YD-38/CIS. The 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay was used to assess cell viability, while trypan blue exclusion assay was used to evaluate cytotoxicity. Flow cytometry and western blot analysis measured apoptotic cell death. Wound-healing assays evaluated cell migration and EMT markers. Combination index (CI) plots were used to evaluate the combinatory effects of the treatment. Combination therapy significantly reduced cell viability more effectively than each agent alone, as demonstrated by the MTT assay, with CI plots confirming notable synergism. Trypan blue exclusion assays indicated increased cell death and cytotoxicity in combination treatment than in both monotherapies, although the increase was not significant. Flow cytometry and western blot analysis revealed no significant synergistic effect on apoptotic cell death. However, wound-healing assays revealed that the combination of cisplatin and SH003 significantly inhibited cell migration and regulated EMT markers, indicating the potential reversal of EMT. Combining cisplatin and SH003 therapy may potentially be a more effective strategy for treating cisplatin-resistant cancer by increasing cytotoxicity and inhibiting metastasis. Further research is required to elucidate the underlying mechanisms and evaluate the in vivo efficacy of this combination therapy.

Noninvasive Method Using Mechanical Extensometer for the Estimation of Intracranial Compliance by Repeated Measures Agreement Analysis.

Intracranial compliance refers to the relationship between changes in volume and the resultant changes in intracranial pressure (ICP). This study aimed to assess the agreement of a noninvasive ICP waveform device for the estimation of compliance compared with invasive ICP monitoring employing three distinct methods. We conducted a retrospective analysis of ICP waveform morphology recorded through both invasive (external ventricular drain) and noninvasive (mechanical extensometer) methods in adult patients with acute brain injury admitted to a neurointensive care unit between August 2021 and August 2022. Compliance was calculated as the amplitude of the fundamental component of cerebral arterial blood volume (estimated with concurrent Transcranial Doppler [TCD] recordings), divided by the amplitude of the fundamental component of the invasive and noninvasive ICP waveforms. Subsequently, we assessed the agreement between invasive and noninvasive intracranial compliance by repeated measures correlation coefficient analysis using three methods: TCD-derived, P2/P1 ratio, and time-to-peak (TTP). A linear mixed-effects model was used to compute the concordance correlation coefficient, total deviation index, and coefficient of individual agreement. Coverage probability plot was calculated to estimate the percent of observations within different cut points for each of the three methods. A total of 21 patients were identified for this study. Repeated measures correlation analysis showed a strong correlation (R = 0.982, 95% confidence interval [0.980-0.984], p < 0.0001) between log-transformed noninvasive and invasive compliance. Agreement statistics for TCD, P2/P1 ratio, and TTP indicated that although the concordance correlation coefficient was highest for log(TCD) values, TTP and P2:P1 ratio measures had better agreement with total deviation index and coverage probability plot analyses. Repeated measures correlations suggest that ICP waveform analyses may offer a more accurate estimate of compliance than TCD-derived methods for noninvasive ICP monitoring. Further validations studies are warranted to confidently establish this method as an indicator of intracranial compliance.

Defining the exit meta-analysis.

In recent decades, clinical research has seen significant advancements, both in the generation and synthesis of evidence through meta-analyses. Despite these methodological advancements, there is a growing concern about the accumulation of repetitive and redundant literature, potentially contributing to research waste. This highlights the necessity for a mechanism to determine when a meta-analysis has conclusively addressed a research question, signaling no further need for additional studies-a concept we term an "exit" meta-analysis. We introduced a convergence index, the Doi-Abdulmajeed Trial Stability (DAts) index, and a convergence plot to determine the exit status of a meta-analysis. The performance of DAts was examined through simulation and applied to two real-world meta-analyses. The DAts index and convergence plot demonstrate highly effective discriminative ability across varying study scenarios. This represents the first attempt to define an exit meta-analysis using a quantitative measurement of stability (as opposed to sufficiency) and its corresponding plot. The application to real-world scenarios further validated the utility of DAts and the convergence plot in identifying a conclusive (exit) meta-analyses. The new development of DAts and the convergence plot provide a promising tool for investigating the conclusiveness of meta-analyses. By identifying an exit status for meta-analysis, the scientific community may be equipped to make better-informed decisions on the continuation of research on a specific topic, thereby preventing research waste and focusing efforts on areas with unresolved questions.

Carbon dioxide storage and cumulative oil production predictions in unconventional reservoirs applying optimized machine-learning models

To achieve carbon dioxide (CO2) storage through enhanced oil recovery, accurate forecasting of CO2 subsurface storage and cumulative oil production is essential. This study develops hybrid predictive models for the determination of CO2 storage mass and cumulative oil production in unconventional reservoirs. It does so with two multi-layer perceptron neural networks (MLPNN) and a least-squares support vector machine (LSSVM), hybridized with grey wolf optimization (GWO) and/or particle swarm optimization (PSO). Large, simulated datasets were divided into training (70%) and testing (30%) groups, with normalization applied to both groups. Mahalanobis distance identifies/eliminates outliers in the training subset only. A non-dominated sorting genetic algorithm (NSGA-II) combined with LSSVM selected seven influential features from the nine available input parameters: reservoir depth, porosity, permeability, thickness, bottom-hole pressure, area, CO2 injection rate, residual oil saturation to gas flooding, and residual oil saturation to water flooding. Predictive models were developed and tested, with performance evaluated with an overfitting index (OFI), scoring analysis, and partial dependence plots (PDP), during training and independent testing to enhance model focus and effectiveness. The LSSVM-GWO model generated the lowest root mean square error (RMSE) values (0.4052 MMT for CO2 storage and 9.7392 MMbbl for cumulative oil production) in the training group. That trained model also exhibited excellent generalization and minimal overfitting when applied to the testing group (RMSE of 0.6224 MMT for CO2 storage and 12.5143 MMbbl for cumulative oil production). PDP analysis revealed that the input features “area” and “porosity” had the most influence on the LSSVM-GWO model's prediction performance. This paper presents a new hybrid modeling approach that achieves accurate forecasting of CO2 subsurface storage and cumulative oil production. It also establishes a new standard for such forecasting, which can lead to the development of more effective and sustainable solutions for oil recovery.

Validation of the Danish Version of the Overall Depression Severity and Impairment Scale (ODSIS): A Reliable Instrument for Assessing Depression Symptoms and Functional Impairment.

In psychotherapy, having a reliable tracking tool is vital for effective treatment. We have validated the Danish version of the 'Overall Depression Severity and Impairment Scale' (ODSIS), which is used in the Unified Protocol for Emotional Disorders (UP) and other cognitive behavioural therapies. This five-item self-rating scale is expected to correspond closely to the gold-standard Beck Depression Inventory-II (BDI-II), but also to self-rating scales addressing daily functioning and well-being. Internal consistency is assessed using Cronbach's alpha and McDonald's omega. Criterion validity is explored through Pearson's correlation coefficient with BDI-II, the Work and Social Adjustment Scale (WSAS), the Five-Item World Health Organization Well-Being Index (WHO-5) and scatter plots, and an optimal cut-off score is determined using a receiver operating characteristic curve. The study included 340 respondents: 234 from a recent clinical trial, 56 psychiatric patients from inpatient/outpatient units and 50 healthy volunteers. ODSIS demonstrates strong internal consistency (Cronbach's alpha: 0.887-0.956, McDonald's omega: 0.888-0.957). Correlations with BDI-II, WSAS and WHO-5 highlight its strong criterion validity (BDI-II: 0.847, WSAS: 0.751, WHO-5: 0.771). The optimal cut-off score (> 7.5) for detecting depression shows great sensitivity (0.862) and specificity (0.731). The Danish version of ODSIS proves to be a reliable instrument for quantification of a combination of depression level and functional impairment from the symptoms. Its high correlation with established BDI-II makes it a brief and handy tool for repeated measurement in clinical and research settings.

A novel prediction model for the probability of aggressive behavior in patients with mood disorders: Based on a cohort study

BackgroundAccurately predicting the probability of aggressive behavior is crucial for guiding early intervention in patients with mood disorders. MethodsCox stepwise regression was conducted to identify potential influencing factors. Nomogram prediction models were constructed to predict the probabilities of aggressive behavior in patients with mood disorders, and their performance was assessed using consistency index (C-index) and calibration plots. ResultsResearch findings on 321 patients with mood disorders indicated that being older (HR = 0.92, 95% CI: 0.86–0.98), single (HR = 0.11, 95% CI: 0.02–0.68), having children (one child, HR = 0.07, 95%CI: 0.01–0.87; more than one child, HR = 0.33, 95%CI: 0.04–2.48), living in dormitory (HR = 0.25, 95%CI: 0.08–0.77), non-student (employee, HR = 0.24, 95% CI: 0.07–0.88; non-employee, HR = 0.09, 95% CI: 0.02–0.35), and higher scores in subjective support (HR = 0.90, 95% CI: 0.82–0.99) were protective factors. On the contrary, minorities (HR = 5.26, 95% CI: 1.23–22.48), living alone (HR = 4.37, 95% CI: 1.60–11.94), having suicide history (HR = 2.51, 95% CI: 1.06–5.95), and having higher scores in EPQ-E (HR = 1.04, 95% CI: 1.00–1.08) and EPQ-P (HR = 1.03, 95% CI: 1.00–1.07) were identified as independent risk factors for aggressive behavior in patients with mood disorders. The nomogram prediction model demonstrated high discrimination and goodness-of-fit. ConclusionsA novel nomogram prediction model for the probability of aggressive behavior in patients with mood disorders was developed, effective in identifying at-risk populations and offering valuable insights for early intervention and proactive measures.

Unexpected Ag-H bond in the predictive silver hydride phase under high pressure

Silver, typically acknowledged for its inertness toward hydrogen under standard conditions, exhibits a noteworthy shift in reactivity under elevated pressures. Employing first-principles variable-composition evolutionary search calculations, our investigation unveils the presence of thermodynamically stable Ag-H compounds. A novel stoichiometry, Ag2H, characterized by P3¯m1 symmetry, emerges as the thermodynamically stable phase at 100 GPa. Notably, the trigonal-Ag2H phase at 100 GPa demonstrates both mechanical and dynamic stability, as ascertained through the computation of elastic constants and phonon dispersions, respectively. Examination of the electronic band structure and density of states manifests the metallic nature of the resulting Ag2H compound. A comprehensive analysis involving crystal orbital bond index, Bader charge, and charge density plots substantiates the ionic character of Ag2H, attributable to effective charge transfer from silver atoms to hydrogen. Furthermore, application of the Allen-Dynes modified McMillan equation indicates the absence of superconducting behavior in Ag-H systems at the elevated pressure of 100 GPa.

Seasonal and Time-Series Analysis of Road Traffic Accidents

Road Traffic Accidents (RTAs) contribute a significant and escalating rate in harm, hospitalization, and mortality. This study assesses the seasonal trend and time series analysis of RTAs cases brought to casualty department of Liaquat University Hospital, Hyderabad, Pakistan. Objective: To conduct seasonal and time series analysis of RTA cases at Casualty Department of Liaquat University Hospital Hyderabad. Methods: Nine hundred and sixty-six road traffic accidents-related cases were examined through prospective study at casualty department, Liaquat University Hospital, Hyderabad, Pakistan from January 2020 to December 2022. The seasonal trend was demonstrated by drawing seasonal index plot and time series plot. Results: The largest occurrences of RTA-related cases were reported in the month of December, having 103 total cases with a mean of 34.33 ± 18.92. July had the second highest frequency of RTAs-related cases, with a total of 94 cases having a mean of 31 ± 5.43 cases. The second-highest number of cases was observed in July and November with approximately equal mean number of RTAs. The time series analysis demonstrated an increasing trend of RTAs-related cases in the last three months of the year. Conclusions: The number of cases connected to RTAs increased during seasons of extreme weather, such as the summer and winter, and it also showed an increasing tendency in the last quarter of 2022.

Nomograms based on ratio indexes to predict severity and prognosis in immune checkpoint inhibitors-related myocarditis: a retrospective analysis

PurposeImmune checkpoint inhibitors-related myocarditis (ICI-M) is one of the immune-related adverse events (irAEs), which is rare and highly lethal. This study aimed to establish nomograms based on ratio biomarkers to predict the severity and prognosis of ICI-M.MethodsWe retrospectively examined patients with advanced cancers who were also diagnosed with ICI-M at the Fourth Hospital of Hebei Medical University. The patients of ICI-M were divided into mild and severe groups and a 40-day following up was carried out. The major adverse cardiovascular events(MACEs) were regarded as the endpoint. Nomogram-based models were established and validated.ResultsSeventy-seven patients were involved, including 31 severe cases(40.3%). Lactate dehydrogenase-to-albumin ratio(LAR) combined with the change rate from baseline to onset of LAR(▵\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ riangle$$\\end{document}LAR) which performed best to diagnose the severe ICI-M was identified to establish the nomogram-based model. The bootstrap-corrected concordance index [0.752 95% confidence interval (CI): 0.635-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}0.866] and calibration plot with good degree of fitting confirmed this diagnostic model. Neutrophil-to-high-density lipoprotein cholesterol ratio(NHR) and LAR were also screened into the nomogram-based model for 40-day MACEs after ICI-M, which performed well by validating for concordance index(0.779 95% CI: 0.677-\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$-$$\\end{document}0.865)and calibration plots after being bootstrap-corrected. Moreover, a ≥\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\ge$$\\end{document}101% increase in LAR significantly separated patients in MACE-free survival.ConclusionRatio indexes at onset and their change rates from baseline showed good diagnostic value for the severity of ICI-M and prognostic value for subsequent MACEs, particularly LAR, NHR and their change rates. The nomogram-based models of ratio indexes could provide a potential choice for early detection and monitor of the severe ICI-M and subsequent MACEs.Graphical abstract

Organic petrographic and mineralogical composition of the No. 6 coal seam of the Soutpansberg Coalfield, South Africa: Insights into paleovegetation and depositional environment

This study investigates the paleodepositional conditions of the No. 6 Seam of the Madzaringwe Formation in Makhado and Voorburg south area of the Soutpansberg Coalfield (Limpopo Province, South Africa) utilizing organic petrography and inorganic geochemical proxies. The coals are predominantly high-volatile bituminous B-A rank with high ash yields (avg. 36.1 wt%), characterized by high-vitrinite (~ 41.5 vol%), moderate-to-high inertinite (9.8 vol%–33.7 vol%) and low liptinite (~ 2.3 vol%). The distribution of inertinite varies among different coal horizons (from bottom-lower to middle-upper), suggesting differential oxidation conditions and/or paleofire occurrence. Vitrinite-to-inertinite (V/I) ratio, tissue preservation–gelification index (TPI–GI), and groundwater–vegetation index (GWI–VI) plots, indicate that the peat-forming forest-swamp vegetation accumulated under mesotrophic-to-rheotrophic hydrological conditions. The presence of structured macerals (i.e., telinite, collotelinite, fusinite, and semifusinite) suggests well-preserved plant tissues, whereas framboidal pyrite and sulphur content (0.24 wt%–2.16 wt%) point to brackish-water influence at the peat stage. The coals contain quartz, kaolinite, siderite, muscovite, dolomite, calcite, and pyrite minerals, most of which were likely sourced from felsic igneous rocks. The Al/(Al+Fe+Mn) and (Fe+Mn)/Ti ratios for the studied samples range between 0.24–0.97 and 0.57–70.10, respectively. The ratios, Al–Fe–Mn plot, and presence of massive botryoidal-type pyrite imply some influence of meteoric waters or fluids from hydrothermal activity post-deposition. Moreover, the chemical index of alteration (CIA: 98.25–99.67), chemical index of weathering (CIW: 92.04–97.66), and A–CN–K ternary diagram suggest inorganic matter suffered strong chemical weathering, indicating warm paleoclimatic conditions during the coal formation.

Bivariate extreme value analysis of extreme temperature and mortality in Canada, 2000-2020.

Climate change increases the risk of illness through rising temperature, severe precipitation and worst air pollution. This paper investigates how monthly excess mortality rate is associated with the increasing frequency and severity of extreme temperature in Canada during 2000-2020. The extreme associations were compared among four age groups across five sub-blocks of Canada based on the datasets of monthly T90 and T10, the two most representative indices of severe weather monitoring measures developed by the actuarial associations in Canada and US. We utilize a combined seasonal Auto-regressive Integrated Moving Average (ARIMA) and bivariate Peaks-Over-Threshold (POT) method to investigate the extreme association via the extreme tail index and Pickands dependence function plots. It turns out that it is likely (more than 10%) to occur with excess mortality if there are unusual low temperature with extreme intensity (all except Northeast Atlantic (NEA), Northern Plains (NPL) and Northwest Pacific (NWP) for age group 0-44), while extreme frequent high temperature seems not to affect health significantly (all except NWP). Particular attention should be paid to NWP and Central Arctic (CAR) since population health therein is highly associated with both extreme frequent high and low temperatures (both for all age groups). The revealed extreme dependence is expected to help stakeholders avoid significant ramifications with targeted health protection strategies from unexpected consequences of extreme weather events. The novel extremal dependence methodology is promisingly applied in further studies of the interplay between extreme meteorological exposures, social-economic factors and health outcomes.

Comparing Visual and Software-Based Quantitative Assessment Scores of Lungs' Parenchymal Involvement Quantification in COVID-19 Patients.

(1) Background: Computed tomography (CT) plays a paramount role in the characterization and follow-up of COVID-19. Several score systems have been implemented to properly assess the lung parenchyma involved in patients suffering from SARS-CoV-2 infection, such as the visual quantitative assessment score (VQAS) and software-based quantitative assessment score (SBQAS) to help in managing patients with SARS-CoV-2 infection. This study aims to investigate and compare the diagnostic accuracy of the VQAS and SBQAS with two different types of software based on artificial intelligence (AI) in patients affected by SARS-CoV-2. (2) Methods: This is a retrospective study; a total of 90 patients were enrolled with the following criteria: patients' age more than 18 years old, positive test for COVID-19 and unenhanced chest CT scan obtained between March and June 2021. The VQAS was independently assessed, and the SBQAS was performed with two different artificial intelligence-driven software programs (Icolung and CT-COPD). The Intraclass Correlation Coefficient (ICC) statistical index and Bland-Altman Plot were employed. (3) Results: The agreement scores between radiologists (R1 and R2) for the VQAS of the lung parenchyma involved in the CT images were good (ICC = 0.871). The agreement score between the two software types for the SBQAS was moderate (ICC = 0.584). The accordance between Icolung and the median of the visual evaluations (Median R1-R2) was good (ICC = 0.885). The correspondence between CT-COPD and the median of the VQAS (Median R1-R2) was moderate (ICC = 0.622). (4) Conclusions: This study showed moderate and good agreement upon the VQAS and the SBQAS; enhancing this approach as a valuable tool to manage COVID-19 patients and the combination of AI tools with physician expertise can lead to the most accurate diagnosis and treatment plans for patients.

Advancing necrotizing enterocolitis prediction through iterative monitoring.

Necrotizing enterocolitis (NEC) is a severe inflammatory intestinal disease in preterm infants, marked by heightened morbidity and mortality. Timely prediction of NEC is significant in the management of critical neonates. However, it is difficult to predict NEC accurately because of the multi-factorial pathogenesis. This study aimed to develop a prediction model through repeated measurement data to further improve the accuracy of prediction in NEC. We retrospectively collected clinical data of premature infants admitted to the Neonatology Department of the First Affiliated Hospital of Anhui Medical University from January 2016 to December 2023. The infants were categorized into the NEC group (Bell's stage ≥ II) (n=150) and the non-NEC group (n=150). The clinical baseline data of the NEC and non-NEC groups were matched. Laboratory examination indicators were collected on the 1st day, the 7th day after birth, and the day of NEC onset. Univariate and multivariate logistic regression analyses were conducted to identify independent factors influencing NEC. A nomogram was constructed based on these factors to predict NEC. The concordance index and calibration plot were used to assess the efficiency of the nomogram in the training and validation cohorts. This study demonstrated that antenatal steroids, antenatal antibiotics, probiotics treatment before NEC, anion gap (AG, day 7), and mean corpuscular volume (MCV, day 7) were independent risk factors which combined to accurately predict NEC. A nomogram of NEC was created utilizing these five predictors. With an area under the receiver operator characteristic (ROC) curve of 0.835 [95% confidence interval (CI): 0.785-0.884]. Concordance index for the training and validation groups were 0.835 and 0.848, respectively. As the calibration plots indicate, the predicted probability of NEC is highly consistent with the actual observation. The risk estimation nomogram for NEC offers clinical value by guiding early prediction, targeted prevention, and early intervention strategies for NEC.

Unlocking the future of hepatocellular carcinoma treatment: A comprehensive analysis of disulfidptosis-related lncRNAs for prognosis and drug screening.

The disulfide stress-induced cell death known as disulfidptosis is characterized by the disintegration of cytoskeletal proteins and F-actin as a result of an excessive buildup of disulfides within the cell. The relationship between disulfidptosis-associated long non-coding RNA (lncRNA) in hepatocellular carcinoma (HCC) progression is still not clearly understood. In this article, we aim to explore the crucial role of lncRNA in HCC. We initially obtained lncRNA related to HCC and clinical data from TCGA. The genes associated with disulfidptosis were identified through co-expression analysis, Cox regression, and Lasso regression. Additionally, we established a prognostic model for verification. The risk model constructed with disulfidptosis-related lncRNA has been confirmed to be a good predictor of high and low-risk groups of HCC patients through survival curves, independent prognostic analysis, concordance index (C-index), ROC curves, and Kaplan-Meier plots. We also discovered differences in the response to immune targets and anticancer drugs between the two groups of patients, with GDC0810, Osimertinib, Paclitaxel, and YK-4-279 being more effective for patients in the high-risk group. In conclusion, we have developed a risk model that can guide future efforts to diagnose and treat HCC.

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. The prognostic risk score model included 12 genes: TDO2, CHIT1, CARML2, HLA-C, ADIRF, C19orf33, CA8, AHNAK2, RHOV, OPLAH, THEM6, and NEBL. The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically CD8+ T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including CD274 and CTLA4, suggesting that immunotherapy may yield enhanced efficacy within this particular group. In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.

Fascinating inclusion of metal–organic complex moieties in dinuclear Mn(II) and Zn(II) compounds involving pyridinedicarboxylates and phenanthroline: Experimental and theoretical studies

In the present study, we have reported the synthesis of two new dinuclear Mn(II) and Zn(II) metal–organic compounds, [Mn(2,5-PDC)(phen)2][Mn(phen)2(H2O)2]2Cl·10H2O (1) and [Zn(phen)3][Zn(2,6-PDC)2]·11.5H2O (2) (where, 2,5-PDC = 2,5-pyridinedicarboxylate, 2,6-PDC = 2,6-pyridinedicarboxylate, phen = 1,10-phenanthroline) at room temperature which have been characterized by elemental analysis, TGA, spectroscopic (FTIR, electronic) and single crystal X-ray diffraction techniques. A fascinating chloride-water supramolecular cluster in 1 and (H2O)13 H-bonded cluster in 2 along with π-stacked assemblies stabilize the solid state structures. The most interesting aspect of the crystal structure of 1 is the inclusion of complex cationic moieties within the infinite self-assembled chloride-water cluster. Similarly the inclusion of cationic complex moieties in compound 2 inside the supramolecular cavity formed by the anionic complex provides rigidity to the crystal structure. DFT calculations, molecular electrostatic potential (MEP) surface analysis, quantum theory of atoms-in-molecules (QTAIM) and the non-covalent index plot (NCI plot) analysis were performed to investigate the supramolecular assemblies of the compounds. The studies reveal that the antiparallel π-stacking interactions are energetically significant synthons for the assemblies. However, the assemblies in 2 have been dominated mostly by Columbic attraction of the cationic and anionic complex moieties.

Chemical similarity-based design of materials for organic solar cells: Visualizing the generated chemical space of polymers

Potential candidates for photovoltaic applications can be found using chemical similarity analysis. Compounds with similar structural characteristics may perform similarly. Designing of materials for organic solar cells (OSCs) is a difficult and time-consuming process. An existing polymer database is mined to find polymers for OSCs, three polymers (PM6, PBT7-Th, and D18) are used as standard. However, good polymers are not found from this database. A large database of polymers is generated using an automatic method that is implemented on RDkit. Synthetic accessibility of generated polymers is calculated. Similarity analysis is conducted to search the polymers from the generated database. Similarity analysis is performed using Tanimoto index. Large number of potential candidates for polymer solar cells are found. Structure Activity Landscape Index (SALI) plot is used to quantitatively characterize activity landscapes.

Prognostic factors and nomogram construction for primary retroperitoneal myxoid/round cell liposarcoma: an analysis of population-based data

Background: It has been reported that the prognosis for myxoid/round cell liposarcoma (MLPS/RCLPS) is inconsistent across different sites. However, there are neither prognostic studies nor predictive models that focused on MLPS/RCLPS of retroperitoneal origin. Methods: Utilizing the Surveillance, Epidemiology, and End Results database, we selected 171 primary retroperitoneal MLPS/RCLPS cases from the period between 2000 and 2019. Prognostic factors influencing disease-specific survival were identified through Cox regression analysis. These independent prognostic factors were then used to construct a DSS nomogram prediction model. The accuracy and reliability of this nomogram were evaluated using the concordance index (C-index) and calibration plots. Furthermore, we categorized patient prognosis using an X-tile based on the nomogram score. Results: The observed 5-year and 10-year DSS rates for all patients were 64.0% (95% CI: 56.2% – 71.8%) and 47.1% (95% CI: 38.1% – 56.1%), respectively. The patient cohort had a median age of 64 years, ranging from 24 to 92 years, with a slight male predominance (n = 92, 53.8%) over females (n = 79, 46.2%). Distant metastases were diagnosed in 24 patients (14%). The distribution of MLPS and RCLPS was 89.5% and 10.5%, respectively. In terms of treatment, adjuvant radiotherapy was administered to 33 patients (19.3%), neoadjuvant radiotherapy to 9 patients (5.3%), and chemotherapy to 20 patients (11.7%), while a significant majority (83.6%) underwent surgical procedures. Independent prognostic factors for DSS included age (HR = 1.039, P &lt; 0.001), marital status (P = 0.029), history of previous tumors (HR = 0.257, P = 0.007), presence of metastatic disease (HR = 2.206, P = 0.027), and surgical treatment (HR = 0.490, P = 0.036). A nomogram prediction model was constructed to forecast 1-, 5-, and 10-year DSS rates, with a C-index of 0.739. Calibration plots demonstrated a strong correlation between the nomogram’s predictions and actual observations. Based on the prediction model, patients were stratified into three groups, and significant differences in prognosis were observed between these groups. Conclusion: A poorer prognosis is associated with retroperitoneal-derived MLPS/RCLPS than with other sites. The nomogram prediction model we built can be used to assist patients in consulting with their doctors and selecting patients for clinical trials. Relevance for Patients: Our study highlights the unique challenges and prognosis variations in retroperitoneal myxoid/RCLPS. The developed nomogram serves as a valuable tool for patients, aiding informed discussions with doctors and guiding decisions on treatment and clinical trial participation.