Base on photothermal interfacial molecular transfer for efficient biodiesel catalysis via enzyme@cyclodextrin metal-organic frameworks loaded MXene.

Efficient, green and stable catalysis has always been the core concept of enzyme catalysis in industrial processes for manufacturing. Therefore, we construct a new strategy with photothermal interfacial molecular transfer for green and efficient biodiesel catalysis. We encapsulate Candida albicans lipase B (CalB) in a γ-cyclodextrin metal-organic framework (γ-CD-MOF) loading with Ti3C2TX by in situ growth and electrostatic assembly. The γ-CD-MOF not only protects the fragile enzyme, but also enhances the catalytic performance through the synergistic effects of porous adsorption (MOF pore structure) and interfacial enrichment (cyclodextrins host-guest assembly structure) for accelerating substrate transfer (642.6 %). The CalB@γ-CD-MOF/MXene-i activity can be regulated up to 274.6 % by exposure to near-infrared (NIR). Importantly, CalB@γ-CD-MOF/MXene-i achieves 93.3 % biodiesel conversion under NIR and maintained 86.9 % activity after 6 cycles. Meanwhile, the MXene after the CalB@γ-CD-MOF/MXene catalytic cycle can be almost completely recovered. We verify the mechanism of high catalytic activity of γ-CD-MOF and rationalize the mechanism of CD molecular channel by DFT. Therefore, this highly selective enzyme catalytic platform offers new possibilities for green and efficient preparation of bioenergy.

One-Pot Total Synthesis of Natural Products Nitramarine, Nitraridine, and Analogues via a Cascade Oxidation/Pictet-Spengler Condensation/Annulation Process.

A cascade oxidation/Pictet-Spengler condensation/annulation process has been developed for the one-pot total synthesis of nitramarine, nitraridine, and their analogues. The procedure proceeded with easily available quinolines and tryptophan derivatives. A simple and metal-free approach, wide substrate scope, and functional group tolerance make it applicable for the synthesis of diverse bioactive nitramarine, nitraridine, and their derivatives. Furthermore, the bioactivity evaluation has identified two promising leading compounds 5d and 5e with potent antitumor proliferative activity against breast cancer cells.

"NO" controversy? : a controversial role in insulin signaling of diabetic encephalopathy.

Insulin, a critical hormone in the human body, exerts its effects by binding to insulin receptors and regulating various cellular processes. While nitric oxide (NO) plays an important role in insulin secretion and acts as a mediator in the signal transduction pathway between upstream molecules and downstream effectors, holds a significant position in the downstream signal network of insulin. Researches have shown that the insulin-NO system exhibits a dual regulatory effect within the central nervous system, which is crucial in the regulation of diabetic encephalopathy (DE). Understanding this system holds immense practical importance in comprehending the targets of existing drugs and the development of potential therapeutic interventions. This review extensively examines the characterization of insulin, NO, Nitric oxide synthase (NOS), specific NO pathway, their interconnections, and the mechanisms underlying their regulatory effects in DE, providing a reference for new therapeutic targets of DE.

Cell-cell communication: new insights and clinical implications.

Multicellular organisms are composed of diverse cell types that must coordinate their behaviors through communication. Cell-cell communication (CCC) is essential for growth, development, differentiation, tissue and organ formation, maintenance, and physiological regulation. Cells communicate through direct contact or at a distance using ligand-receptor interactions. So cellular communication encompasses two essential processes: cell signal conduction for generation and intercellular transmission of signals, and cell signal transduction for reception and procession of signals. Deciphering intercellular communication networks is critical for understanding cell differentiation, development, and metabolism. First, we comprehensively review the historical milestones in CCC studies, followed by a detailed description of the mechanisms of signal molecule transmission and the importance of the main signaling pathways they mediate in maintaining biological functions. Then we systematically introduce a series of human diseases caused by abnormalities in cell communication and their progress in clinical applications. Finally, we summarize various methods for monitoring cell interactions, including cell imaging, proximity-based chemical labeling, mechanical force analysis, downstream analysis strategies, and single-cell technologies. These methods aim to illustrate how biological functions depend on these interactions and the complexity of their regulatory signaling pathways to regulate crucial physiological processes, including tissue homeostasis, cell development, and immune responses in diseases. In addition, this review enhances our understanding of the biological processes that occur after cell-cell binding, highlighting its application in discovering new therapeutic targets and biomarkers related to precision medicine. This collective understanding provides a foundation for developing new targeted drugs and personalized treatments.

Supportive Psychotherapy Combined with Analgesic Management can Effectively Improve Pain and Quality of Life in Patients with Advanced Prostate Cancer: A Retrospective Study.

OBJECTIVE: Patients with advanced prostate cancer commonly experience psychological issues and have a low quality of life. This study aims to analyse the application of supportive psychotherapy combined with analgesic management on the pain and quality of life of patients with advanced prostate cancer. METHODS: Patients with advanced prostate cancer admitted to our hospital from February 2018 to December 2022 were continuously selected as the research objects. In accordance with the different management methods recorded in the medical record system, the patients were divided into a control group (routine nursing + analgesic management) and an observation group (routine nursing + analgesic management + supportive psychotherapy). The Athens Insomnia Scale (AIS), State Anxiety Scale (S-AI), Trait Anxiety Scale (T-AI), Numeric Rating Scale (NRS) and 36-Item Short-Form Health Survey (SF-36) scores between the two groups were compared. RESULTS: A total of 125 patients with advanced prostate cancer participated in this study, with 60 patients in the control group and 65 patients in the observation group. No significant difference was found in the scores of the AIS, S-AI, T-AI, NRS and SF-36 of the two groups before management (p > 0.05). After management, the AIS (4.00 vs. 5.00, p = 0.002), S-AI (38.88 vs. 41.12, p = 0.002), T-AI (39.17 vs. 41.65, p = 0.001) and NRS (3.00 vs. 3.00, p < 0.001) scores of the observation group were lower than those of the control group. However, the SF-36 scores of the observation group were higher than those of the control group in the dimensions of physiological enginery (75.85 vs. 68.75, p < 0.001), physiological function (71.85 vs. 67.75, p = 0.004), body pain (73.15 vs. 69.33, p = 0.006), social function (73.88 vs. 69.85, p = 0.004), emotional function (72.92 vs. 68.98, p = 0.006), mental health (73.52 vs. 69.83, p = 0.008), vitality (72.09 vs. 69.52, p = 0.044) and general health (70.65 vs. 66.23, p = 0.002). CONCLUSIONS: Supportive psychotherapy combined with analgesic management for patients with advanced prostate cancer may help improve the pain, anxiety and quality of sleep and life of patients.

The combined effect of triglyceride-glucose index and high-sensitivity C-reactive protein on cardiovascular outcomes in patients with chronic coronary syndrome: A multicenter cohort study.

BACKGROUND: The triglyceride-glucose (TyG) index and high-sensitivity C-reactive protein (hsCRP) are the commonly used biomarkers for insulin resistance and systemic inflammation, respectively. We aimed to investigate the combined association of TyG and hsCRP with the major adverse cardiovascular events (MACE) in patients with chronic coronary syndrome (CCS). METHODS: A total of 9421 patients with CCS were included in this study. The primary endpoint was defined as a composite of MACE covering all-cause death, nonfatal myocardial infarction, and revascularization. RESULTS: During the 2-year follow-up period, 660 (7.0%) cases of MACE were recorded. Participants were divided equally into three groups according to TyG levels. Compared with the TyG T1 group, the risk of MACE was significantly higher in the TyG T3 group. It is noteworthy that among patients in the highest tertile of TyG, hsCRP >3 mg/L was significantly associated with an increased risk of MACE, whereas the results were not significant in the medium to low TyG groups. When patients were divided into six groups according to hsCRP and TyG, the Cox regression analysis showed that patients in the TyG T3 and hsCRP >3 mg/L group had a significantly higher risk of MACE than those in the TyG T1 and hsCRP ≤3 mg/L group. However, no significant interaction was found between TyG and hsCRP on the risk of MACE. CONCLUSION: Our study suggests that the concurrent assessment of TyG and hsCRP may be valuable in identifying high-risk populations and guiding management strategies among CCS patients.

Inducible RPE-specific GPX4 knockout causes oxidative stress and retinal degeneration with features of age-related macular degeneration.

Age-related macular degeneration (AMD) is one of the leading causes of vision loss in the elderly. This disease involves oxidative stress burden in the retina leading to death of retinal pigment epithelial (RPE) cells and photoreceptors. The retina is susceptible to oxidative stress, in part due to high metabolic activity and high concentration of polyunsaturated fatty acids that undergo lipid peroxidation chain reactions. Antioxidant enzymes exist in the retina to combat this stress, including glutathione peroxidase 4 (GPX4). GPX4 specifically reduces oxidized lipids, protecting against lipid peroxidation-induced oxidative stress, which is noted in dry AMD. We hypothesize that Gpx4 knockout within the RPE will result in an environment of chronic oxidative stress yielding degeneration akin to AMD. C57BL/6J mice with a floxed Gpx4 gene were mated with Rpe65Cre/ER mice. Offspring containing Rpe65Cre ± alleles and either Gpx4 WT or Gpx4 fl/fl alleles were administered tamoxifen to induce Gpx4 knockout in Gpx4 fl/fl mice. At sequential timepoints, retinal phenotypes were assessed via in vivo imaging utilizing confocal scanning laser ophthalmoscopy and optical coherence tomography (OCT), and visual function was probed by electroretinography. Retinas were studied post-mortem by immunohistochemical analyses, electron microscopy, plastic sectioning, and quantitative polymerase chain reaction and Western analyses. The RPE-specific Gpx4 knockout model was validated via Western analysis indicating diminished GPX4 protein only within the RPE and not the neural retina. Following Gpx4 knockout, RPE cells became dysfunctional and died, with significant cell loss occurring 2 weeks post-knockout. Progressive thinning of the photoreceptor layer followed RPE degeneration and was accompanied by loss of visual function. OCT and light microscopy showed hyperreflective foci and enlarged, pigmented cells in and above the RPE layer. Electron microscopy revealed decreased mitochondrial cristae and loss of basal and apical RPE ultrastructure. Finally, there was increased carboxyethylpyrrole staining, indicating oxidation of docosahexaenoic acid, and increased levels of mRNAs encoding oxidative stress-associated genes in the RPE and photoreceptors. Overall, we show that RPE-localized GPX4 is necessary for the health of the RPE and outer retina, and that knockout recapitulates phenotypes of dry AMD.

Prospects of Pseudomonas in Microbial Fuel, Bioremediation, and Sustainability.

Microbial applications in agriculture and industry have gained significant attention due to their potential to address environmental challenges and promote sustainable development. Among these, the genus Pseudomonas stands out as a promising candidate for various biotechnological uses, thanks to its metabolic flexibility, resilience, and adaptability to diverse environments. This review provides a comprehensive overview of the current state and future prospects of microbial fuel production, bioremediation, and sustainable development, focusing on the pivotal role of Pseudomonas species. We emphasize the importance of microbial fuel as a renewable energy source and discuss recent advancements in enhancing biofuel generation using Pseudomonas strains. Additionally, we explore the critical role of Pseudomonas in bioremediation processes, highlighting its ability to degrade a wide spectrum of pollutants, including hydrocarbons, pesticides, and heavy metals, thereby reducing environmental contamination. Despite significant progress, several challenges remain. These include refining microbial strains for optimal process efficiency and addressing ecological considerations. Nonetheless, the diverse capabilities of Pseudomonas offer promising avenues for innovative solutions to pressing environmental issues, supporting the transition to a more sustainable future.

Epidemic spreading on spatial higher-order network.

Higher-order interactions exist widely in mobile populations and are extremely important in spreading epidemics, such as influenza. However, research on high-order interaction modeling of mobile crowds and the propagation dynamics above is still insufficient. Therefore, this study attempts to model and simulate higher-order interactions among mobile populations and explore their impact on epidemic transmission. This study simulated the spread of the epidemic in a spatial high-order network based on agent-based model modeling. It explored its propagation dynamics and the impact of spatial characteristics on it. Meanwhile, we construct state-specific rate equations based on the uniform mixing assumption for further analysis. We found that hysteresis loops are an inherent feature of high-order networks in this space under specific scenarios. The evolution curve roughly presents three different states with the initial value change, showing different levels of the endemic balance of low, medium, and high, respectively. Similarly, network snapshots and parameter diagrams also indicate these three types of equilibrium states. Populations in space naturally form components of different sizes and isolations, and higher initial seeds generate higher-order interactions in this spatial network, leading to higher infection densities. This phenomenon emphasizes the impact of high-order interactions and high-order infection rates in propagation. In addition, crowd density and movement speed act as protective and inhibitory factors for epidemic transmission, respectively, and depending on the degree of movement weaken or enhance the effect of hysteresis loops.

[Spatial Prediction and Influencing Factors Analysis of Soil Salinization in Coastal Area Based on MGWR].

Quantitative analysis of the spatial non-stationary characteristics of soil salinization influencing factors and the prediction of its spatial distribution are of great significance for the rational use of coastal saline soil resources and the formulation of local prevention and control measures. In this study, the Hekou District of Dongying City, Shandong Province, was used as the study area, and the descriptive statistics of soil salinization status were conducted using classical statistical methods. Spatial autocorrelation theory was used to explore the characteristics of global and local spatial structure of soil salinization in the study area. Influential factors related to soil salinity were selected, and multivariate linear regression （MLR）, geographically weighted regression （GWR）, and multi-scale geographically weighted regression （MGWR） methods were used to model and predict the spatial distribution of soil salinity in the study area and to analyze the spatial heterogeneity of the effects of different influencing factors on soil salinity. The results showed that： ① The mean value of soil salinity in the study area was 5.84 g·kg-1, indicating severe salinization, with a global Moran's I index of 0.19 （P<0.00） and obvious spatial aggregation characteristics. ② Among the three models, the MGWR model had the highest modeling accuracy. Compared with that of the MLR model, the Radj2 of GWR and MGWR improved by 0.05 and 0.07, respectively, and the RSS decreased by 210.13 and 179.95, respectively. ③ The results of MGWR regression showed that the spatial distribution of soil salinity appeared to be mainly affected by the middle soil salinity, soil clay content, and vegetation cover from the mean values of standardized regression coefficients of different influencing factors. Different influencing factors had significant spatial non-stationary characteristics on soil salinization. ④ The results of the spatial distribution prediction of soil salinity in MGWR showed that the areas of high soil salinity （≥6 g·kg-1） were mainly distributed in the northern part of the study area, with an overall spatial trend of decreasing from the coast to the interior. The results of the study can be used as a reference for the analysis and predictive mapping of factors affecting soil salinization in the county and on a larger scale using MGWR.

Cost-effectiveness of dostarlimab plus chemotherapy for primary advanced or recurrent endometrial cancer.

Objective: In the double-blind, phase III, placebo-controlled RUBY randomized clinical trial, dostarlimab plus carboplatin-paclitaxel significantly increased survival among patients with primary advanced or recurrent endometrial cancer (EC). We conducted a cost-effectiveness analysis of dostarlimab in combination with chemotherapy in these patients stratified by mismatch repair-deficient (dMMR) and mismatch repair-proficient (pMMR) subgroups from the perspective of a United States payer. Materials and methods: A Markov model with three states was employed to simulate patients who were administered either dostarlimab in combination with chemotherapy or chemotherapy based on the RUBY trial. Quality-adjusted life-years (QALYs), lifetime costs, and incremental cost-effectiveness ratio (ICER) were calculated with a willingness-to-pay (WTP) threshold of $150,000 per QALY. Both univariate and probabilistic sensitivity analyses were carried out to explore the robustness of the model. Results: In dMMR EC, the combination of dostarlimab and chemotherapy achieved an additional 5.48 QALYs at an incremental cost of $330,747 compared to chemotherapy alone, resulting in an ICER of $60,349.30 per QALY. In pMMR EC, there were 1.51 additional QALYs gained at an extra cost of $265,148, yielding an ICER of $175,788.47 per QALY. With a 15.2% discount on dostarlimab, the ICER decreased to $150,000 per QALY in the pMMR EC. The univariate sensitivity analysis revealed that the cost of dostarlimab, utility of progression-free survival (PFS), and progressive disease (PD) had the most significant impacts on the outcomes. Probabilistic sensitivity analysis revealed that dostarlimab had a 100% likelihood of being considered cost-effective for patients at a WTP threshold of $150,000 per QALY for dMMR EC, whereas this likelihood was only 0.5% for pMMR EC. Conclusion: Dostarlimab in combination with chemotherapy was cost-effective for primary advanced or recurrent dMMR EC from the perspective of a United States payer at a WTP threshold of $150,000 per QALY, but not for pMMR EC. Lowering the prices of dostarlimab could potentially enhance the cost-effectiveness of treatment for pMMR EC.

Cardiorespiratory motion characteristics and their dosimetric impact on cardiac stereotactic body radiotherapy.

BACKGROUND: Cardiac stereotactic body radiotherapy (CSBRT) is an emerging and promising noninvasive technique for treating refractory arrhythmias utilizing highly precise, single or limited-fraction high-dose irradiations. This method promises to revolutionize the treatment of cardiac conditions by delivering targeted therapy with minimal exposure to surrounding healthy tissues. However, the dynamic nature of cardiorespiratory motion poses significant challenges to the precise delivery of dose in CSBRT, introducing potential variabilities that can impact treatment efficacy. The complexities of the influence of cardiorespiratory motion on dose distribution are compounded by interplay and blurring effects, introducing additional layers of dose uncertainty. These effects, critical to the understanding and improvement of the accuracy of CSBRT, remain unexplored, presenting a gap in current clinical literature. PURPOSE: To investigate the cardiorespiratory motion characteristics in arrhythmia patients and the dosimetric impact of interplay and blurring effects induced by cardiorespiratory motion on CSBRT plan quality. METHODS: The position and volume variations in the substrate target and cardiac substructures were evaluated in 12 arrhythmia patients using displacement maximum (DMX) and volume metrics. Moreover, a four-dimensional (4D) dose reconstruction approach was employed to examine the dose uncertainty of the cardiorespiratory motion. RESULTS: Cardiac pulsation induced lower DMX than respiratory motion but increased the coefficient of variation and relative range in cardiac substructure volumes. The mean DMX of the substrate target was 0.52 cm (range: 0.26-0.80 cm) for cardiac pulsation and 0.82 cm (range: 0.32-2.05 cm) for respiratory motion. The mean DMX of the cardiac structure ranged from 0.15 to 1.56 cm during cardiac pulsation and from 0.35 to 1.89 cm during respiratory motion. Cardiac pulsation resulted in an average deviation of -0.73% (range: -4.01%-4.47%) in V25 between the 3D and 4D doses. The mean deviations in the homogeneity index (HI) and gradient index (GI) were 1.70% (range: -3.10%-4.36%) and 0.03 (range: -0.14-0.11), respectively. For cardiac substructures, the deviations in D50 due to cardiac pulsation ranged from -1.88% to 1.44%, whereas the deviations in Dmax ranged from -2.96% to 0.88% of the prescription dose. By contrast, the respiratory motion led to a mean deviation of -1.50% (range: -10.73%-4.23%) in V25. The mean deviations in HI and GI due to respiratory motion were 4.43% (range: -3.89%-13.98%) and 0.18 (range: -0.01-0.47) (p < 0.05), respectively. Furthermore, the deviations in D50 and Dmax in cardiac substructures for the respiratory motion ranged from -0.28% to 4.24% and -4.12% to 1.16%, respectively. CONCLUSIONS: Cardiorespiratory motion characteristics vary among patients, with the respiratory motion being more significant. The intricate cardiorespiratory motion characteristics and CSBRT plan complexity can induce substantial dose uncertainty. Therefore, assessing individual motion characteristics and 4D dose reconstruction techniques is critical for implementing CSBRT without compromising efficacy and safety.

Enhanced sludge granulation and stable performance of an anammox expanded granular sludge bed (EGSB) reactor through the utilization of hydroxyapatite (HAP) particles.

The reuse of hydroxyapatite particles (HAPs) as a granulation activator for anammox sludge was explored to address the remaining issues of time-consuming and unstable granular structure in anammox granulation. During the granulation, nitrogen removal capacity from 2.8 to 13.7 gN/L/d was obtained within 193 days, accompanied by an enhancement in bio-activity from 0.23 to 0.52 gN/gVSS/d. HAPs and anammox microorganisms coupled well to aggregate into granules for denser biomass, higher settleability, and stronger mechanical properties, which effectively improved the biomass retention capacity and structural strength of the sludge system. A skeleton structure formed by the HAPs was characterized during the transformation of the granules, playing a crucial role in strengthening the stability of the sludge. The intermediate processes of granulation were thus clarified to propose an evolutionary pathway for anammox-HAP granules. The pre-addition of HAPs is conducive to achieving faster anammox granulation and rapid process start-up for high-strength wastewater treatment.

Quantifying dose uncertainties resulting from cardiorespiratory motion in intensity-modulated proton therapy for cardiac stereotactic body radiotherapy.

Background: Cardiac stereotactic body radiotherapy (CSBRT) with photons efficaciously and safely treats cardiovascular arrhythmias. Proton therapy, with its unique physical and radiobiological properties, can offer advantages over traditional photon-based therapies in certain clinical scenarios, particularly pediatric tumors and those in anatomically challenging areas. However, dose uncertainties induced by cardiorespiratory motion are unknown. Objective: This study investigated the effect of cardiorespiratory motion on intensity-modulated proton therapy (IMPT) and the effectiveness of motion-encompassing methods. Methods: We retrospectively included 12 patients with refractory arrhythmia who underwent CSBRT with four-dimensional computed tomography (4DCT) and 4D cardiac CT (4DcCT). Proton plans were simulated using an IBA accelerator based on the 4D average CT. The prescription was 25 Gy in a single fraction, with all plans normalized to ensure that 95% of the target volume received the prescribed dose. 4D dose reconstruction was performed to generate 4D accumulated and dynamic doses. Furthermore, dose uncertainties due to the interplay effect of the substrate target and organs at risk (OARs) were assessed. The differences between internal organs at risk volume (IRV) and OARreal (manually contoured on average CT) were compared. In 4D dynamic dose, meeting prescription requirements entails V25 and D95 reaching 95% and 25 Gy, respectively. Results: The 4D dynamic dose significantly differed from the 3D static dose. The mean V25 and D95 were 89.23% and 24.69 Gy, respectively, in 4DCT and 94.35% and 24.99 Gy, respectively, in 4DcCT. Eleven patients in 4DCT and six in 4DcCT failed to meet the prescription requirements. Critical organs showed varying dose increases. All metrics, except for Dmean and D50, significantly changed in 4DCT; in 4DcCT, only D50 remained unchanged with regards to the target dose uncertainties induced by the interplay effect. The interplay effect was only significant for the Dmax values of several OARs. Generally, respiratory motion caused a more pronounced interplay effect than cardiac pulsation. Neither IRV nor OARreal effectively evaluated the dose discrepancies of the OARs. Conclusions: Complex cardiorespiratory motion can introduce dose uncertainties during IMPT. Motion-encompassing techniques may mitigate but cannot entirely compensate for the dose discrepancies. Individualized 4D dose assessments are recommended to verify the effectiveness and safety of CSBRT.

Luminescent fiber UV detection.

Herein, a luminescent fiber device for detecting ultraviolet (UV) intensity, which comprises a UV probe and a photoelectric converter, is proposed. The UV probe consists of a glass tube filled with luminescent material, which can be used for the efficient radiation conversion of UV radiation to the visible spectral region. The luminescent material, Y2O2S:Eu3+, is mixed with polydimethylsiloxane (PDMS) to form the core of the UV probe. Subsequently, the UV radiation response of the luminescent fiber device is investigated; the experimental results demonstrate that the direction-independent UV detection can be realized by using this luminescent fiber UV detection device while UV light is radiated radially along the UV probe. In addition, since partial discharge (PD) is accompanied by UV radiation, we hope to develop a spectral PD detection scheme based on optical fiber technology, which can broaden the role of optical technology and optical fiber technology in the field of PD detection.

GAPS: a geometric attention-based network for peptide binding site identification by the transfer learning approach.

Protein-peptide interactions (PPepIs) are vital to understanding cellular functions, which can facilitate the design of novel drugs. As an essential component in forming a PPepI, protein-peptide binding sites are the basis for understanding the mechanisms involved in PPepIs. Therefore, accurately identifying protein-peptide binding sites becomes a critical task. The traditional experimental methods for researching these binding sites are labor-intensive and time-consuming, and some computational tools have been invented to supplement it. However, these computational tools have limitations in generality or accuracy due to the need for ligand information, complex feature construction, or their reliance on modeling based on amino acid residues. To deal with the drawbacks of these computational algorithms, we describe a geometric attention-based network for peptide binding site identification (GAPS) in this work. The proposed model utilizes geometric feature engineering to construct atom representations and incorporates multiple attention mechanisms to update relevant biological features. In addition, the transfer learning strategy is implemented for leveraging the protein-protein binding sites information to enhance the protein-peptide binding sites recognition capability, taking into account the common structure and biological bias between proteins and peptides. Consequently, GAPS demonstrates the state-of-the-art performance and excellent robustness in this task. Moreover, our model exhibits exceptional performance across several extended experiments including predicting the apo protein-peptide, protein-cyclic peptide and the AlphaFold-predicted protein-peptide binding sites. These results confirm that the GAPS model is a powerful, versatile, stable method suitable for diverse binding site predictions.

Comparison of four confirmatory tests for the diagnosis of primary aldosteronism: Bayesian analysis in the absence of a gold standard.

BACKGROUND: Captopril challenge test (CCT), seated saline infusion test (SSIT), oral sodium loading test (OSLT) and fludrocortisone suppression test (FST) are widely used diagnostic tests for primary aldosteronism (PA). These tests differ in terms of safety and complexity. Whether the simpler tests (CCT and SSIT) are comparable in diagnostic performance to the more complex ones (FST and OSLT) is unclear. PURPOSE: To compare the diagnostic accuracy of the four tests. METHODS: This is a retrospective study of hypertensive patients who were screened for PA and completed at least one confirmatory test. The patients were divided into two cohorts: one including those who completed one to three tests was used for the estimation of sensitivity and specificity. The other including those who completed four tests was used for the comparison of accuracy. Bayesian method was used to obtain the sensitivity, specificity, and Youden index of each test. RESULTS: The study included 1011 hypertensive patients. Among them, 895 patients completed one to three tests (including 889 CCT, 605 FST, 611 SSIT and 69 OSLT), and 116 patients completed four tests. SSIT had the highest sensitivity of 0.82(95% CI 0.78-0.86) but the lowest specificity of 0.76(0.70-0.80). OSLT had the lowest sensitivity of 0.65(0.56-0.75) but the highest specificity of 0.91(0.82-0.96). The sensitivity and specificity were 0.78 (95% CI, 0.75-0.82), 0.82 (95% CI, 0.78-0.85), for CCT, and 0.77 (95% CI, 0.73-0.81), 0.87 (95% CI, 0.82-0.91) for FST, respectively. The Youden index was not significantly different among the four tests[0.60(0.55-0.65) for CCT; 0.58(0.51-0.64) for SSIT; (0.64(0.57-0.69) for FST; 0.56(0.43-0.67) for OSLT]. CONCLUSION: The accuracy of simpler tests is comparable to the more complex ones. Considering the safety and simplicity of CCT, it may be a reasonable first choice when confirming the diagnosis of PA.

Serum neurofilament light chain levels are associated with depression among US adults: a cross-sectional analysis among US adults, 2013-2014.

BACKGROUND: Serum neurofilament light chain (sNfL) has been identified as a biomarker for neurologic diseases. However, sNfL remains unknown to be responsible for depression. AIMS: The aim of this research was to explore the relationship between sNfL levels and depression in US adults. METHODS: In this cross-sectional survey of the general population, we investigated representative data involving 10,175 participants from the 2013-2014 cycle of the National Health and Nutrition Examination Survey (NHANES). Depression was diagnosed using the Patient Health Questionnaire-9 (PHQ-9). The effect of related factors on depression was analyzed by conducting a univariate analysis. Stratified analysis was utilized to detect the stability and sensitivity of the relationship. After adjusting for race, education, marital status, smoking status, body mass index (BMI), sleep duration, income, and a history of hypertension, sedentary behavior and stroke, multivariable linear regression was performed to demonstrate the correlation between sNfL and depression. RESULTS: A total of 1301 individuals between the ages of 20 and 75 were involved in this investigation, of which 108 (8.3%) were diagnosed with depression. A significant positive correlation between sNfL and depression among adults in the US was observed by conducting univariable analyses. After adjusting for confounding factors, the multivariate analyses indicated that elevated sNfL levels might play a pivotal role in the development of depression (odds ratio (OR) = 3.0; 95% confidence interval (CI): (1.5, 6.1), P = 0.002). CONCLUSION: These results indicated that sNfL is closely linked to depression in a nationally representative individual. However, further studies are needed to confirm the biological mechanism as well as the clinical implications of sNfL and depression.

Radiomics analysis combining gray-scale ultrasound and mammography for differentiating breast adenosis from invasive ductal carcinoma.

Objectives: To explore the utility of gray-scale ultrasound (GSUS) and mammography (MG) for radiomic analysis in distinguishing between breast adenosis and invasive ductal carcinoma (IDC). Methods: Data from 147 female patients with pathologically confirmed breast lesions (breast adenosis: 61 patients; IDC: 86 patients) between January 2018 and December 2022 were retrospectively collected. A training cohort of 113 patients (breast adenosis: 50 patients; IDC: 63 patients) diagnosed from January 2018 to December 2021 and a time-independent test cohort of 34 patients (breast adenosis: 11 patients; IDC: 23 patients) diagnosed from January 2022 to December 2022 were included. Radiomic features of lesions were extracted from MG and GSUS images. The least absolute shrinkage and selection operator (LASSO) regression was applied to select the most discriminant features, followed by logistic regression (LR) to construct clinical and radiomic models, as well as a combined model merging radiomic and clinical features. Model performance was assessed using receiver operating characteristic (ROC) analysis. Results: In the training cohort, the area under the curve (AUC) for radiomic models based on MG features, GSUS features, and their combination were 0.974, 0.936, and 0.991, respectively. In the test cohort, the AUCs were 0.885, 0.876, and 0.949, respectively. The combined model, incorporating clinical and all radiomic features, and the MG plus GSUS radiomics model were found to exhibit significantly higher AUCs than the clinical model in both the training cohort and test cohort (p<0.05). No significant differences were observed between the combined model and the MG plus GSUS radiomics model in the training cohort and test cohort (p>0.05). Conclusion: The effectiveness of radiomic features derived from GSUS and MG in distinguishing between breast adenosis and IDC is demonstrated. Superior discriminatory efficacy is shown by the combined model, integrating both modalities.