Differential distribution of PINK1 and Parkin in the primate brain implies distinct roles.

JOURNAL/nrgr/04.03/01300535-202504000-00028/figure1/v/2024-07-06T104127Z/r/image-tiff The vast majority of in vitro studies have demonstrated that PINK1 phosphorylates Parkin to work together in mitophagy to protect against neuronal degeneration. However, it remains largely unclear how PINK1 and Parkin are expressed in mammalian brains. This has been difficult to address because of the intrinsically low levels of PINK1 and undetectable levels of phosphorylated Parkin in small animals. Understanding this issue is critical for elucidating the in vivo roles of PINK1 and Parkin. Recently, we showed that the PINK1 kinase is selectively expressed as a truncated form (PINK1-55) in the primate brain. In the present study, we used multiple antibodies, including our recently developed monoclonal anti-PINK1, to validate the selective expression of PINK1 in the primate brain. We found that PINK1 was stably expressed in the monkey brain at postnatal and adulthood stages, which is consistent with the findings that depleting PINK1 can cause neuronal loss in developing and adult monkey brains. PINK1 was enriched in the membrane-bound fractionations, whereas Parkin was soluble with a distinguishable distribution. Immunofluorescent double staining experiments showed that PINK1 and Parkin did not colocalize under physiological conditions in cultured monkey astrocytes, though they did colocalize on mitochondria when the cells were exposed to mitochondrial stress. These findings suggest that PINK1 and Parkin may have distinct roles beyond their well-known function in mitophagy during mitochondrial damage.

Parental health penalty on adult children's employment: Gender differences and long-term consequences.

This study examines the gender-specific and enduring impacts of parental health shocks on adult children's employment in China, where both formal care and health insurance are limited. Using an event-study approach, we establish a causal link between parental health shocks and a notable decline in female employment, which persists for at least six years following the shock. Male employment, however, exhibits minimal change on average, although this conceals an increase among poor families, indicating a channel beyond heightened informal care. Our findings underscore the consequences of "growing old before getting rich" for developing countries.

Effect and mechanism of phosphate enhanced sulfite activation with cobalt ion for effective iohexol abatement.

Sulfate radical (SO4•-)-based advanced oxidation processes (AOPs) from sulfite activation have recently received attention for abatement of microorganic pollutants in the aquatic environments. Trace-level Co(II) has been demonstrated to be effective for promoting sulfite activation (simplified as the Co(II)/sulfite system) and the corresponding radical formation, yet this process is challenged by the limited valence inter-transformation of Co(II)/Co(III). In order to enhance this valence inter-transformation, a novel Co(II)/HPO42-/sulfite system is developed in this work, because HPO42-, as a typical radical scavenging agent, has the advantage of complexing with Co(II) without quenching effect. In this work, complexation of Co(II) with HPO42- can regulate the electronic structure of Co(II), accelerate electron transfer, and promote valence inter-transformation of Co(II)/Co(III) during the sulfite activation process. The Co(II)/HPO42-/sulfite system exhibits superior iohexol abatement performance under circumneutral conditions. For pH 8.0 and Co(II) dose of 1 µM, the iohexol abatement efficiency is as high as 98%, which is considerably higher than that of the Co(II)/sulfite system (50%). SO4•- is identified as the predominant reactive radical contributing to iohexol abatement. The presence of HPO42- broadens the pH adaptability of the Co(II)/sulfite system for iohexol abatement. In addition, the coexisting Cl- exerts an inhibitory effect on iohexol abatement while the other cations and anions show negligible effect. The Co(II)/HPO42-/sulfite system displays good reusability and adaptability towards various organic pollutants. This study highlights the important role of complexation of Co(II) with HPO42- in sulfite activation and provides a feasible idea for abatement of the microorganic pollutants.

Prediction model of ocular metastasis from primary liver cancer: Machine learning-based development and interpretation study.

BACKGROUND: Ocular metastasis (OM) is a rare metastatic site of primary liver cancer (PLC). The purpose of this study was to establish a clinical predictive model of OM in PLC patients based on machine learning (ML). METHODS: We retrospectively collected the clinical data of 1540 PLC patients and divided it into a training set and an internal test set in a 7:3 proportion. PLC patients were divided into OM and non-ocular metastasis (NOM) groups, and univariate logistic regression analysis was performed between the two groups. The variables with univariate logistic analysis p < 0.05 were selected for the ML model. We constructed six ML models, which were internally verified by 10-fold cross-validation. The prediction performance of each ML model was evaluated by receiver operating characteristic curves (ROCs). We also constructed a web calculator based on the optimal performance ML model to personalize the risk probability for OM. RESULTS: Six variables were selected for the ML model. The extreme gradient boost (XGB) ML model achieved the optimal differential diagnosis ability, with an area under the curve (AUC) = 0.993, accuracy = 0.992, sensitivity = 0.998, and specificity = 0.984. Based on these results, an online web calculator was constructed by using the XGB ML model to help clinicians diagnose and treat the risk probability of OM in PLC patients. Finally, the Shapley additive explanations (SHAP) library was used to obtain the six most important risk factors for OM in PLC patients: CA125, ALP, AFP, TG, CA199, and CEA. CONCLUSION: We used the XGB model to establish a risk prediction model of OM in PLC patients. The predictive model can help identify PLC patients with a high risk of OM, provide early and personalized diagnosis and treatment, reduce the poor prognosis of OM patients, and improve the quality of life of PLC patients.

Primary Treatment for Clinically Early Cervical Cancer with Lymph Node Metastasis: Radical Surgery or Radiation?

OBJECTIVE: To compare survival outcomes between primary radical surgery and primary radiation in early cervical cancer. METHODS: Patient information was extracted from the Surveillance, Epidemiology, and Results database. Patients diagnosed with early cervical cancer of stage T1a, T1b, and T2a (American Joint Committee on Cancer, 7th edition) from 1998 to 2015 were included in this study after propensity score matching. Overall survival (OS) was analyzed using the Kaplan-Meier method. RESULTS: Among the 4964 patients included in the study, 1080 patients were identified as having positive lymph nodes (N1), and 3884 patients were identified as having negative lymph nodes (N0). Patients with primary surgery had significantly longer 5-year OS than those with primary radiotherapy in both the N1 group (P<0.001) and N0 group (P<0.001). In the subgroup analysis, similar results were found in patients with positive lymph nodes of stage T1a (100.0% vs. 61.1%), T1b (84.1% vs. 64.3%), and T2a (74.4% vs. 63.8%). In patients with T1b1 and T2a1, primary surgery resulted in longer OS than primary radiation, but not in patients with T1b2 and T2a2. In multivariate analysis, the primary treatment was identified as an independent prognostic factor in both N1 and N0 patients (HRN1=2.522, 95% CI=1.919-3.054, PN1<0.001; HRN0=1.895, 95% CI=1.689-2.126, PN0<0.001). CONCLUSION: In early cervical cancer stage T1a, T1b1, and T2a1, primary surgery may result in longer OS than primary radiation for patients with and without lymph node metastasis.

Effects of whole-body vibration training on cognitive function: A systematic review.

Background: Whole-body vibration (WBV) training is a novel training method that stimulates the human neuromuscular system by the use of vibration, the frequency and amplitude of which are controlled, thereby inducing adaptive changes in the body. WBV training is widely used as a clinical prevention and rehabilitation tool in physical medicine and neuro-rehabilitation as a clinical prevention and rehabilitation tool. Objectives: The aim of the present study was to review the effects of WBV on cognitive function, provide an evidence-based foundation for future research on WBV training, and promote additional popularization and use of the methodology in clinical practice. Methods: A systematic review of articles extracted from the following six databases was conducted: PubMed, Web of Science, China National Knowledge Infrastructure, Embase, Cochrane, and Scopus. A literature search was performed on articles in which the effects of WBV on cognitive function were evaluated. Results: Initially, a total of 340 studies were initially identified, among which 18 articles that satisfied the inclusion criteria were selected for inclusion in the systematic review. Participants were allocated into two groups: patients with cognitive impairment and healthy individuals. The results demonstrated that WBV was both positive and ineffective in its influence on cognitive function. Conclusion: The majority of studies suggested that WBV may be a useful strategy for the management of cognitive impairment and should be considered for inclusion in rehabilitation programs. However, the impact of WBV on cognition requires additional, larger, and adequately powered studies. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=376821, identifier CRD42022376821.

Dynamic Navigation and Area Assignment of Multiple USVs Based on Multi-Agent Deep Reinforcement Learning.

The unmanned surface vehicle (USV) has attracted more and more attention because of its basic ability to perform complex maritime tasks autonomously in constrained environments. However, the level of autonomy of one single USV is still limited, especially when deployed in a dynamic environment to perform multiple tasks simultaneously. Thus, a multi-USV cooperative approach can be adopted to obtain the desired success rate in the presence of multi-mission objectives. In this paper, we propose a cooperative navigating approach by enabling multiple USVs to automatically avoid dynamic obstacles and allocate target areas. To be specific, we propose a multi-agent deep reinforcement learning (MADRL) approach, i.e., a multi-agent deep deterministic policy gradient (MADDPG), to maximize the autonomy level by jointly optimizing the trajectory of USVs, as well as obstacle avoidance and coordination, which is a complex optimization problem usually solved separately. In contrast to other works, we combined dynamic navigation and area assignment to design a task management system based on the MADDPG learning framework. Finally, the experiments were carried out on the Gym platform to verify the effectiveness of the proposed method.

Surface functional groups determine adsorption of pharmaceuticals and personal care products on polypropylene microplastics.

The pervasiveness of microplastics (MPs), which can absorb pharmaceuticals and personal care products (PPCPs), has a certain impact on pollutant migration in natural waters. The adsorption behaviors of PPCPs on the aged polypropylene (PP) followed the pseudo-second-order kinetics and Langmuir isotherm, and the adsorption capacity (qe) on the aged PP was much higher than that on the fresh PP. The Weber-Morris and Boyd models confirmed that the liquid-film and intra-particle diffusion affected the adsorption of PPCPs on the aged PP while the surface diffusion was a rate-limiting step for the fresh PP. The analysis of SEM-EDS, BET, FT-IR, and XPS further showed that changes in the type and content of the surface functional groups of PP led to differences in adsorption capacity and adsorption interactions. The Dragon-descriptor-based LFER and the quantum-chemical-descriptor-based QSAR models reflected the difference in adsorption interaction mechanisms. The examined models showed that the adsorption of the fresh PP toward PPCPs relied on hydrophobic and hydrogen bonding interaction, while for the aged PP electrostatic interaction and hydrogen bonding controlled the adsorption. The findings clarified interactions between PPCPs and MPs and provided a theoretical basis for the assessment of environmental behavior and ecological risk when MPs and PPCPs coexist.

The difference in the adsorption mechanisms of magnetic ferrites modified carbon nanotubes.

Various ferrites modified carbon nanotubes (MFe2O4/CNTs; M = Co, Cu, Mn) were synthesized and characterized using TEM-EDS, FTIR, BET, TG-DTA, VSM, and XRD. MFe2O4/CNTs were used as adsorbents for removing ciprofloxacin (CIP), and the adsorption mechanism was revealed in a comparative manner based on the experimental results and density functional theory calculations. The adsorption capacities of CIP on MFe2O4/CNTs were 63.32 (Co), 61.60 (Cu), and 46.35 (Mn) mg/g, respectively. Different M components of MFe2O4 affected the adsorption behavior of CIP on them, while the specific surface area and total pore volume showed no significant impact. The investigation on the adsorption energy and the bond formation indicated that CIP was more favorably captured by CoFe2O4/CuFe2O4 than MnFe2O4. The local density of states of metal atoms and O atoms (from the ketone or carboxyl groups of CIP) showed that the d-band centers of Co and Cu atoms were above the Fermi level, while that of Mn was below the Fermi level, providing the fundamental understanding of the promoted O adsorption on CoFe2O4 and CuFe2O4 and restrained adsorption on MnFe2O4. This observation was supported by the electron localization function in terms of the stronger charge density overlap between Co-O/Cu-O than that of Mn-O.

Interactive effects of increasing atmospheric CO2 and copper exposure on the growth and photosynthesis in the young sporophytes of Sargassum fusiforme (Phaeophyta).

Little attention has been given to the combined effects of elevated atmospheric CO2-induced ocean acidification (OA) and heavy metal pollution on marine macroalgae at the young stage. This study investigated the mutual effects of copper (Cu) and elevated CO2 on the young sporophytes of brown macroalgae Sargassum fusiforme. A matrix of four copper concentrations, 0, 0.025, 0.075 and 0.15 mg‧L-1, and two levels of CO2 (ambient CO2: 400 µatm; elevated CO2: 1,000 µatm) were used. High concentration of copper exposure greatly depressed photosynthesis and growth of the young sporophytes of S. fusiforme by reducing the apparent photosynthetic efficiency (ɑ), maximum net photosynthetic oxygen evolution rate (Pmax), maximum photochemical quantum yield (Fv/Fm) and pigments content (Chl a and Car). While elevated CO2 alone had obscure impact on this alga. However, the inhibition of Cu stress on Fv/Fm was weakened by elevated CO2, which also decreased the light compensation point (Ic). Meanwhile, the Cu2+-induced ascent in the dark respiration rate (Rd) and superoxide dismutase (SOD) activity was mitigated under the growth with elevated CO2, suggesting an alleviated oxidative stress. Overall, we propose that, under CO2 enrichment condition, the young sporophytes of S. fusiforme may increase photosynthesis efficiency and synthesize less enzymatic antioxidants in face of increasing Cu stress.

The impact of elevated atmospheric CO2 on cadmium toxicity in Pyropia haitanensis (Rhodophyta).

Cadmium is one of the major heavy metal pollutions in coastal waters, and it is well known that cadmium at trace concentration is toxic to macroalgae. Change in marine carbonate system and ocean acidification caused by elevated atmospheric CO2 also alter physiological characteristics of macroalgae. However, less research is focused on the combined impacts of elevated CO2 and cadmium pollution on the growth and physiology in macroalgae. In this study, the maricultivated macroalga Pyropia haitanensis (Rhodophyta) was cultured at three levels of Cd2+ (control, 4 and 12 mg L-1) and two concentrations of CO2, the ambient CO2 (AC, 410 ppm) and elevated CO2 (HC, 1100 ppm). The results showed that 12 mg L-1 Cd2+ significantly suppressed the relative growth rate and superoxide dismutase activity in AC-grown P. haitanensis, while such inhibition extents by Cd2+ were alleviated in HC-grown algae. Cd2+ had no effects on efficiency of electron transport (α) and maximum electron transport rate (ETRmax), but α was increased by elevated CO2. Cd2+ dramatically suppressed the maximum net photosynthesis oxygen evolution rate (NPRm) and the minimum saturation irradiance (Ik) when the algal thalli were grown at AC, while such suppression of NPRm by Cd2+ was much decreased when the thalli were grown at HC. Collectively, our results suggested that elevated CO2 would alleviate Cd2+ toxicity on P. haitanensis.

MEAN-FIELD THEORY AND COMPUTATION OF ELECTROSTATICS WITH IONIC CONCENTRATION DEPENDENT DIELECTRICS.

We construct a mean-field variational model to study how the dependence of dielectric coefficient (i.e., relative permittivity) on local ionic concentrations affects the electrostatic interaction in an ionic solution near a charged surface. The electrostatic free-energy functional of ionic concentrations, which is the key object in our model, consists mainly of the electrostatic potential energy and the ionic ideal-gas entropy. The electrostatic potential is determined by Poisson's equation in which the dielectric coefficient depends on the sum of concentrations of individual ionic species. This dependence is assumed to be qualitatively the same as that on the salt concentration for which experimental data are available and analytical forms can be obtained by the data fitting. We derive the first and second variations of the free-energy functional, obtain the generalized Boltzmann distributions, and show that the free-energy functional is in general nonconvex. To validate our mathematical analysis, we numerically minimize our electrostatic free-energy functional for a radially symmetric charged system. Our extensive computations reveal several features that are significantly different from a system modeled with a dielectric coefficient independent of ionic concentration. These include the non-monotonicity of ionic concentrations, the ionic depletion near a charged surface that has been previously predicted by a one-dimensional model, and the enhancement of such depletion due to the increase of surface charges or bulk ionic concentrations.

A self-consistent phase-field approach to implicit solvation of charged molecules with Poisson-Boltzmann electrostatics.

Dielectric boundary based implicit-solvent models provide efficient descriptions of coarse-grained effects, particularly the electrostatic effect, of aqueous solvent. Recent years have seen the initial success of a new such model, variational implicit-solvent model (VISM) [Dzubiella, Swanson, and McCammon Phys. Rev. Lett. 96, 087802 (2006) and J. Chem. Phys. 124, 084905 (2006)], in capturing multiple dry and wet hydration states, describing the subtle electrostatic effect in hydrophobic interactions, and providing qualitatively good estimates of solvation free energies. Here, we develop a phase-field VISM to the solvation of charged molecules in aqueous solvent to include more flexibility. In this approach, a stable equilibrium molecular system is described by a phase field that takes one constant value in the solute region and a different constant value in the solvent region, and smoothly changes its value on a thin transition layer representing a smeared solute-solvent interface or dielectric boundary. Such a phase field minimizes an effective solvation free-energy functional that consists of the solute-solvent interfacial energy, solute-solvent van der Waals interaction energy, and electrostatic free energy described by the Poisson-Boltzmann theory. We apply our model and methods to the solvation of single ions, two parallel plates, and protein complexes BphC and p53/MDM2 to demonstrate the capability and efficiency of our approach at different levels. With a diffuse dielectric boundary, our new approach can describe the dielectric asymmetry in the solute-solvent interfacial region. Our theory is developed based on rigorous mathematical studies and is also connected to the Lum-Chandler-Weeks theory (1999). We discuss these connections and possible extensions of our theory and methods.

Competitive adsorption and ordered packing of counterions near highly charged surfaces: From mean-field theory to Monte Carlo simulations.

Competitive adsorption of counterions of multiple species to charged surfaces is studied by a size-effect-included mean-field theory and Monte Carlo (MC) simulations. The mean-field electrostatic free-energy functional of ionic concentrations, constrained by Poisson's equation, is numerically minimized by an augmented Lagrangian multiplier method. Unrestricted primitive models and canonical ensemble MC simulations with the Metropolis criterion are used to predict the ionic distributions around a charged surface. It is found that, for a low surface charge density, the adsorption of ions with a higher valence is preferable, agreeing with existing studies. For a highly charged surface, both the mean-field theory and the MC simulations demonstrate that the counterions bind tightly around the charged surface, resulting in a stratification of counterions of different species. The competition between mixed entropy and electrostatic energetics leads to a compromise that the ionic species with a higher valence-to-volume ratio has a larger probability to form the first layer of stratification. In particular, the MC simulations confirm the crucial role of ionic valence-to-volume ratios in the competitive adsorption to charged surfaces that had been previously predicted by the mean-field theory. The charge inversion for ionic systems with salt is predicted by the MC simulations but not by the mean-field theory. This work provides a better understanding of competitive adsorption of counterions to charged surfaces and calls for further studies on the ionic size effect with application to large-scale biomolecular modeling.