Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

De novo transcriptome assembly database for 100 tissues from each of seven species of domestic herbivore.

Domesticated herbivores are an important agricultural resource that play a critical role in global food security, particularly as they can adapt to varied environments, including marginal lands. An understanding of the molecular basis of their biology would contribute to better management and sustainable production. Thus, we conducted transcriptome sequencing of 100 to 105 tissues from two females of each of seven species of herbivore (cattle, sheep, goats, sika deer, horses, donkeys, and rabbits) including two breeds of sheep. The quality of raw and trimmed reads was assessed in terms of base quality, GC content, duplication sequence rate, overrepresented k-mers, and quality score distribution with FastQC. The high-quality filtered RNA-seq raw reads were deposited in a public database which provides approximately 54 billion high-quality paired-end sequencing reads in total, with an average mapping rate of ~93.92%. Transcriptome databases represent valuable resources that can be used to study patterns of gene expression, and pathways that are related to key biological processes, including important economic traits in herbivores.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning. / 基于WGCNAå’Œæœºå™¨å­¦ä¹ ç­›é€‰å¸•é‡‘æ£®ç— å ç–«ç›¸å ³å ³é”®åŸºå› .

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. METHODS: This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. RESULTS: A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. CONCLUSIONS: This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Physical frailty, genetic predisposition, and incident dementia: a large prospective cohort study.

Physical frailty and genetic factors are both risk factors for increased dementia; nevertheless, the joint effect remains unclear. This study aimed to investigated the long-term relationship between physical frailty, genetic risk, and dementia incidence. A total of 274,194 participants from the UK Biobank were included. We applied Cox proportional hazards regression models to estimate the association between physical frailty and genetic and dementia risks. Among the participants (146,574 females [53.45%]; mean age, 57.24 years), 3,353 (1.22%) new-onset dementia events were recorded. Compared to non-frailty, the hazard ratio (HR) for dementia incidence in prefrailty and frailty was 1.396 (95% confidence interval [CI], 1.294-1.506, P < 0.001) and 2.304 (95% CI, 2.030-2.616, P < 0.001), respectively. Compared to non-frailty and low polygenic risk score (PRS), the HR for dementia risk was 3.908 (95% CI, 3.051-5.006, P < 0.001) for frailty and high PRS. Furthermore, among the participants, slow walking speed (HR, 1.817; 95% CI, 1.640-2.014, P < 0.001), low physical activity (HR, 1.719; 95% CI, 1.545-1.912, P < 0.001), exhaustion (HR, 1.670; 95% CI, 1.502-1.856, P < 0.001), low grip strength (HR, 1.606; 95% CI, 1.479-1.744, P < 0.001), and weight loss (HR, 1.464; 95% CI, 1.328-1.615, P < 0.001) were independently associated with dementia risk compared to non-frailty. Particularly, precise modulation for different dementia genetic risk populations can also be identified due to differences in dementia risk resulting from the constitutive pattern of frailty in different genetic risk populations. In conclusion, both physical frailty and high genetic risk are significantly associated with higher dementia risk. Early intervention to modify frailty is beneficial for achieving primary and precise prevention of dementia, especially in those at high genetic risk.

Brolucizumab in recalcitrant neovascular age-related macular degeneration-real-world data in Chinese population.

This retrospective study aimed to determine the short-term efficacy and safety of brolucizumab treatment for recalcitrant neovascular age-related macular degeneration (nAMD) in a real-world setting in Taiwan. Recalcitrant nAMD patients who were treated with brolucizumab from November 2021 to August 2022 at Taipei Veterans General Hospital were included. Patients were followed for 3 months after switching to brolucizumab. The primary outcomes were changes in mean best-corrected visual acuity (BCVA) and central retinal thickness (CRT) from baseline to the third month. The secondary outcomes included the incidence of intraocular inflammation (IOI), proportion of patients with subretinal and intraretinal fluid (SRF and IRF), and change in pigment epithelial detachment (PED) height from baseline to the third month. The significance level was considered as p < .05 in all tests. A total of 38 patients (40 eyes) with a mean (±SD) age of 76.3 (±10.84) years were included. The baseline BCVA was 0.92±0.64 logMAR, and the CRT and PED height were 329.0±171.18 and 189.8±114.94 um, respectively. The patients had a significant reduction in CRT and resolution of IRF and SRF from baseline to the third month. There were numerical improvements in mean BCVA and PED height, but they were not significant. The percentages of achieving at least 0.1, 0.2, and 0.3 logMAR (equivalent to 5, 10, 15 ETDRS letters) visual gain were 50%, 37.5%, and 30%, respectively, during the first 3 months of follow-up. No IOI occurred in these patients. This study demonstrated that brolucizumab had good short-term structural and functional efficacy in recalcitrant nAMD patients.

Online Detection of Laser Welding Penetration Depth Based on Multi-Sensor Features.

The accurate online detection of laser welding penetration depth has been a critical problem to which the industry has paid the most attention. Aiming at the laser welding process of TC4 titanium alloy, a multi-sensor monitoring system that obtained the keyhole/molten pool images and laser-induced plasma spectrum was built. The influences of laser power on the keyhole/molten pool morphologies and plasma thermo-mechanical characteristics were investigated. The results showed that there were significant correlations among the variations of the keyhole-molten pool, plasma spectrum, and penetration depth. The image features and spectral features were extracted by image processing and dimension-reduction methods, respectively. Moreover, several penetration depth prediction models based on single-sensor features and multi-sensor features were established. The mean square error of the neural network model built by multi-sensor features was 0.0162, which was smaller than that of the model built by single-sensor features. The established high-precision model provided a theoretical basis for real-time feedback control of the penetration depth in the laser welding process.

Fly-scan high-throughput coded ptychographic microscopy via active micro-vibration and rolling-shutter distortion correction.

Recent advancements in ptychography have demonstrated the potential of coded ptychography (CP) for high-resolution optical imaging in a lensless configuration. However, CP suffers imaging throughput limitations due to scanning inefficiencies. To address this, we propose what we believe is a novel 'fly-scan' scanning strategy utilizing two eccentric rotating mass (ERM) vibration motors for high-throughput coded ptychographic microscopy. The intrinsic continuity of the 'fly-scan' technique effectively eliminates the scanning overhead typically encountered during data acquisition. Additionally, its randomized scanning trajectory considerably reduces periodic artifacts in image reconstruction. We also developed what we believe to be a novel rolling-shutter distortion correction algorithm to fix the rolling-shutter effects. We built up a low-cost, DIY-made prototype platform and validated our approach with various samples including a resolution target, a quantitative phase target, a thick potato sample and biospecimens. The reported platform may offer a cost-effective and turnkey solution for high-throughput bio-imaging.

Total Tau Protein Mediates the Association of Ischemic Cerebrovascular Disease with Cognitive Decline.

Background: Patients with transient ischemic attack (TIA) or ischemic stroke demonstrate an increased risk of cognitive dysfunction. Accumulating evidence indicates that ischemic cerebrovascular disease (ICVD) may interact with the amyloid/tau/neurodegeneration (AT[N]) biomarkers to promote dementia. However, the precise pathological mechanisms remain to be fully characterized. Objective: To elucidate the interrelationships among ICVD, ATN biomarkers in cerebrospinal fluid (CSF), and cognition. Methods: A total of 2524 participants were recruited from the CABLE study. ICVD referred to TIA/ischemic stroke. Cognitive performance was assessed by China Modified Mini-Mental State Examination (CM-MMSE) and Montreal Cognitive Assessment-b (MoCA-b). Multivariate linear regression analyses were performed to evaluate the associations of ICVD with CSF ATN biomarkers and cognition. Causal mediation analyses were used to identify whether the association was mediated by ATN biomarkers. Results: ICVD was associated with higher total-tau (t-tau) (p = 2.828×10-2) and poorer cognition (CM-MMSE: p = 1.539×10-5, MoCA-b: p = 4.552×10-6). Additionally, no discernible correlation surfaced between ICVD and amyloid-ß (Aß) 42 (p = 6.910×10-1) or phosphorylated tau (p-tau) (p = 4.324×10-1). The influence of ICVD on cognitive function was partially mediated by CSF t-tau (CM-MMSE: proportion: 2.74%, MoCA-b: proportion: 2.51%). Subgroup analyses revealed the influences of t-tau were especially evident in male (CM-MMSE: proportion: 5.45%, MoCA-b: proportion: 5.38%) and mid-life group (CM-MMSE: proportion: 9.83%, MoCA-b: proportion: 5.31%). Conclusions: These results delineated t-tau as a potential mediator for the influence of ICVD on cognition. Targeting brain ischemia and alleviating neuronal injury induced by ischemia may be a promising approach for preventing cognitive decline.

Exome sequencing and genome-wide association analyses unveils the genetic predisposition in hydroxychloroquine retinopathy.

OBJECTIVES: To unveil the candidate susceptibility genes in chloroquine/hydroxychloroquine (CQ/HCQ) retinopathy using whole exome sequencing (WES) and genome-wide association study (GWAS). METHODS: Patients with a diagnosis of CQ/HCQ retinopathy based on the comprehensive demographic and ocular examination were included. The peripheral blood was extracted for WES and GWAS analyses. The Chinese Han Southern database from 1000 genomes was used as control group to compare the affected percentage. Multivariate logistic regression analysis adjusted for age, HCQ dose, duration and renal disease were used to analyze the correlation between genetic variants and visual outcome. A poor vision outcome was defined as visual acuity <6/12. An abnormal anatomical outcome was defined as disruption of ellipsoid zone in the fovea. RESULTS: Twenty-nine patients with an average age of 60.9 ± 13.4 years, treatment duration of 12.1 ± 6.2 years, daily dose of 8.5 ± 4.1 mg/kg, and the cumulative dose of 1637.5 ± 772.5 g, were genotyped. Several candidate genes associated with CQ/HCQ retinopathy were found, including RP1L1, RPGR and RPE65, with a difference of affected percentage over 50% in mutation between the case and control groups. New foci in CCDC66: rs56616026 (OR = 63.43, p = 1.63 × 10-8) and rs56616023 (OR = 104.7, p = 5.02 × 10-10) were identified significantly associated with HCQ retinopathy. Multivariate analysis revealed increased genetic variants were significantly associated with poor functional (OR = 1.600, p = 0.004) and structural outcome (OR = 1.318, p = 0.043). CONCLUSIONS: Several candidate susceptibility genes including RP1L1, RPGR, RPE65 and CCDC66 were identified to be associated with CQ/HCQ retinopathy. In addition to disease susceptibility, patients with increased genetic variants are more vulnerable to poor visual outcomes.

Bone mesenchymal stem cell-derived exosomal miR-26a-3p promotes autophagy to attenuate LPS-induced apoptosis and inflammation in pulmonary microvascular endothelial cells.

Acute lung injury (ALI) is a serious lung disease. The apoptosis and inflammation of pulmonary microvascular endothelial cells (PMVECs) are the primary reasons for ALI. This study aimed to explore the treatment effect and regulatory mechanism of bone mesenchymal stem cell-derived exosomes (BMSC-expos) on ALI. PMVECs were stimulated by Lipopolysaccharide (LPS) to imitate ALI environment. Cell viability was determined by CCK-8 assay. Cell apoptosis was evaluated by TUNEL and flow cytometry. ELISA was utilized for testing the contents of TNF-α, IL-1ß, IL-6, and IL-17. Western blot was applied for testing the levels of autophagy-related proteins LC3, p62, and Beclin-1. RNA interaction was determined by luciferase reporter assay. The ALI rat model was established by intratracheal injection of LPS. Evans blue staining was utilized for detecting pulmonary vascular permeability. Our results showed that LPS stimulation notably reduced cell viability, increased cell apoptosis rate, and enhanced the contents of inflammatory factors in PMVECs. However, BMSC-exo treatment significantly abolished the promoting effects of LPS on cell injury. In addition, we discovered that BMSC-exo treatment notably activated autophagy in LPS-induced PMVECs. Furthermore, BMSC-expos upregulated miR-26a-3p expression and downregulated PTEN in PMVECs. MiR-26a-3p was directly bound to PTEN. MiR-26a-3p overexpression reduced cell apoptosis, and inflammation and promoted autophagy by silencing PTEN. Animal experiments proved that miR-26a-3p overexpression effectively improved LPS-induced lung injury in rats. The results proved that BMSC-expos promotes autophagy to attenuate LPS-induced apoptosis and inflammation in pulmonary microvascular endothelial cells via miR-26a-3p/PTEN axis.

Velocities of transmission eigenchannels and diffusion.

The diffusion model is used to calculate both the time-averaged flow of particles in stochastic media and the propagation of waves averaged over ensembles of disordered static configurations. For classical waves exciting static disordered samples, such as a layer of paint or a tissue sample, the flux transmitted through the sample may be dramatically enhanced or suppressed relative to predictions of diffusion theory when the sample is excited by a waveform corresponding to a transmission eigenchannel. Even so, it is widely assumed that the velocity of waves is irretrievably randomized in scattering media. Here we demonstrate in microwave measurements and numerical simulations that the statistics of velocity of different transmission eigenchannels are distinct and remains so on all length scales and are identical on the incident and output surfaces. The interplay between eigenchannel velocities and transmission eigenvalues determines the energy density within the medium, the diffusion coefficient, and the dynamics of propagation. The diffusion coefficient and all scattering parameters, including the scattering mean free path, oscillate with the width of the sample as the number and shape of the propagating channels in the medium change.

Associations of Frailty with Neuropsychiatric Symptoms of Alzheimer's Disease: A Longitudinal Study.

Background: Frailty is a vulnerability state increasing the risk of many adverse health outcomes, but little is known about the effects of frailty on neuropsychiatric health. Objective: To explore the associations between frailty and the risk of neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD), especially in its different clinical stages. Methods: We included 2,155 individuals assessed using modified frailty index-11 (mFI-11), Neuropsychiatric Inventory (NPI) and Neuropsychiatric Inventory Questionnaire (NPI-Q) in the Alzheimer's Disease Neuroimaging Initiative (ADNI). The relationships between frailty and NPSs were explored with logistic regression models and Cox proportional hazard regression models. Causal mediation analyses were conducted to explore the mediation factors between frailty and NPSs. Results: Among mild cognitive impairment (MCI) participants, frailty was cross-sectionally associated with an increased risk of apathy, and longitudinally associated with increased risk of depression and apathy. Among AD participants, frailty was cross-sectionally associated with increased risk of depression and anxiety, and longitudinally associated with an increased risk of apathy. Among participants with cognitive progression, frailty was associated with increased risk of depression and apathy. In MCI participants, the influence of frailty on NPSs was partially mediated by hippocampus volume, whole brain volume, and monocytes, with mediating proportions ranging from 8.40% to 9.29%. Conclusions: Frailty was associated with NPSs such as depression, anxiety, and apathy among MCI, AD, and cognitive progression participants. Atrophy of the hippocampus and whole brain, as well as peripheral immunity may be involved in the potential mechanisms underlying the above associations.

Utilizing microbial metabolite in catalytic cascade synthesis of conjugated oligomers for In-Situ regulation of biological activity.

Despite the advances of multistep enzymatic cascade reactions, their incorporation with abiotic reactions in living organisms remains challenging in synthetic biology. Herein, we combined microbial metabolic pathways and Pd-catalyzed processes for in-situ generation of bioactive conjugated oligomers. Our biocompatible one-pot coupling reaction utilized the fermentation process of engineered E. coli that converted glucose to styrene, which participated in the Pd-catalyzed Heck reaction for in-situ synthesis of conjugated oligomers. This process serves a great interest in understanding resistance evolution by utilizing the inhibitory activity of the synthesized conjugated oligomers. The approach allows for the in-situ combination of biological metabolism and CC coupling reactions, opening up new possibilities for the biosynthesis of unnatural molecules and enabling the in-situ regulation of the bioactivity of the obtained products.

Picea wilsonii NAC31 and DREB2A Cooperatively Activate ERD1 to Modulate Drought Resistance in Transgenic Arabidopsis.

The NAC family of transcription factors (TFs) regulate plant development and abiotic stress. However, the specific function and response mechanism of NAC TFs that increase drought resistance in Picea wilsonii remain largely unknown. In this study, we functionally characterized a member of the PwNAC family known as PwNAC31. PwNAC31 is a nuclear-localized protein with transcriptional activation activity and contains an NAC domain that shows extensive homology with ANAC072 in Arabidopsis. The expression level of PwNAC31 is significantly upregulated under drought and ABA treatments. The heterologous expression of PwNAC31 in atnac072 Arabidopsis mutants enhances the seed vigor and germination rates and restores the hypersensitive phenotype of atnac072 under drought stress, accompanied by the up-regulated expression of drought-responsive genes such as DREB2A (DEHYDRATION-RESPONSIVE ELEMENT BINDING PROTEIN 2A) and ERD1 (EARLY RESPONSIVE TO DEHYDRATION STRESS 1). Yeast two-hybrid and bimolecular fluorescence complementation assays confirmed that PwNAC31 interacts with DREB2A and ABF3 (ABSCISIC ACID-RESPONSIVE ELEMENT-BINDING FACTOR 3). Yeast one-hybrid and dual-luciferase assays showed that PwNAC31, together with its interaction protein DREB2A, directly regulated the expression of ERD1 by binding to the DRE element of the ERD1 promoter. Collectively, our study provides evidence that PwNAC31 activates ERD1 by interacting with DREB2A to enhance drought tolerance in transgenic Arabidopsis.

Mesoporous nanoperforators as membranolytic agents via nano- and molecular-scale multi-patterning.

Plasma membrane lysis is an effective anticancer strategy, which mostly relying on soluble molecular membranolytic agents. However, nanomaterial-based membranolytic agents has been largely unexplored. Herein, we introduce a mesoporous membranolytic nanoperforators (MLNPs) via a nano- and molecular-scale multi-patterning strategy, featuring a spiky surface topography (nanoscale patterning) and molecular-level periodicity in the spikes with a benzene-bridged organosilica composition (molecular-scale patterning), which cooperatively endow an intrinsic membranolytic activity. Computational modelling reveals a nanospike-mediated multivalent perforation behaviour, i.e., multiple spikes induce nonlinearly enlarged membrane pores compared to a single spike, and that benzene groups aligned parallelly to a phospholipid molecule show considerably higher binding energy than other alignments, underpinning the importance of molecular ordering in phospholipid extraction for membranolysis. Finally, the antitumour activity of MLNPs is demonstrated in female Balb/c mouse models. This work demonstrates assembly of organosilica based bioactive nanostructures, enabling new understandings on nano-/molecular patterns co-governed nano-bio interaction.

Sensing, Imaging, and Therapeutic Strategies Endowing by Conjugate Polymers for Precision Medicine.

Conjugated polymers (CPs) have promising applications in biomedical fields, such as disease monitoring, real-time imaging diagnosis, and disease treatment. As a promising luminescent material with tunable emission, high brightness and excellent stability, CPs are widely used as fluorescent probes in biological detection and imaging. Rational molecular design and structural optimization have broadened absorption/emission range of CPs, which are more conductive for disease diagnosis and precision therapy. This review provides a comprehensive overview of recent advances in the application of CPs, aiming to elucidate their structural and functional relationships. The fluorescence properties of CPs and the mechanism of detection signal amplification are first discussed, followed by an elucidation of their emerging applications in biological detection. Subsequently, CPs-based imaging systems and therapeutic strategies are illustrated systematically. Finally, recent advancements in utilizing CPs as electroactive materials for bioelectronic devices are also investigated. Moreover, the challenges and outlooks of CPs for precision medicine are discussed. Through this systematic review, it is hoped to highlight the frontier progress of CPs and promote new breakthroughs in fundamental research and clinical transformation.

Whole-brain spatial organization of hippocampal single-neuron projectomes.

Mapping single-neuron projections is essential for understanding brain-wide connectivity and diverse functions of the hippocampus (HIP). Here, we reconstructed 10,100 single-neuron projectomes of mouse HIP and classified 43 projectome subtypes with distinct projection patterns. The number of projection targets and axon-tip distribution depended on the soma location along HIP longitudinal and transverse axes. Many projectome subtypes were enriched in specific HIP subdomains defined by spatial transcriptomic profiles. Furthermore, we delineated comprehensive wiring diagrams for HIP neurons projecting exclusively within the HIP formation (HPF) and for those projecting to both intra- and extra-HPF targets. Bihemispheric projecting neurons generally projected to one pair of homologous targets with ipsilateral preference. These organization principles of single-neuron projectomes provide a structural basis for understanding the function of HIP neurons.

Simulation of emission reduction path under the path of differentiated energy transformation in China's industrial cities: a case study of Shanghai.

The formulation of long-term step-by-step emission reduction plan is an important step for effective scientific emission reduction. This paper takes Shanghai as the research object, constructs PSO-LSTM model on the basis of STIRPAT model, and further constructs three dynamic policy scenarios combined with China's actual situation and makes short-, medium-, and long-term multivariate predictions for them. The study finds that only the improvement of energy consumption structure has a promotion effect on carbon emission reduction, and urbanization, industrial structure, technology level, population, and economic level all have an increasing effect, and secondly, the carbon emission reduction path of Shanghai basically achieves the core objective of steady decrease under the three scenarios. Secondly, under the three scenarios, Shanghai's carbon emission reduction path basically achieves the core objective of steady decline, but the decline in the GU scenario is more significant. It is recommended that Shanghai further adjusts its industrial structure, optimizes its energy consumption structure, promotes technological innovation and progress, and promotes the development of the circular economy model.

Genetic susceptibility modifies the association of long-term air pollution exposure on Parkinson's disease.

Inconsistent findings exist regarding the potential association between polluted air and Parkinson's disease (PD), with unclear insights into the role of inherited sensitivity. This study sought to explore the potential link between various air pollutants and PD risk, investigating whether genetic susceptibility modulates these associations. The population-based study involved 312,009 initially PD-free participants with complete genotyping data. Annual mean concentrations of PM2.5, PM10, NO2, and NOx were estimated, and a polygenic risk score (PRS) was computed to assess individual genetic risks for PD. Cox proportional risk models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI) for the associations between ambient air pollutants, genetic risk, and incident PD. Over a median 12.07-year follow-up, 2356 PD cases (0.76%) were observed. Compared to the lowest quartile of air pollution, the highest quartiles of NO2 and PM10 pollution showed HRs and 95% CIs of 1.247 (1.089-1.427) and 1.201 (1.052-1.373) for PD incidence, respectively. Each 10 µg/m3 increase in NO2 and PM10 yielded elevated HRs and 95% CIs for PD of 1.089 (1.026-1.155) and 1.363 (1.043-1.782), respectively. Individuals with significant genetic and PM10 exposure risks had the highest PD development risk (HR: 2.748, 95% CI: 2.145-3.520). Similarly, those with substantial genetic and NO2 exposure risks were over twice as likely to develop PD compared to minimal-risk counterparts (HR: 2.414, 95% CI: 1.912-3.048). Findings suggest that exposure to air contaminants heightens PD risk, particularly in individuals genetically predisposed to high susceptibility.

Organic Semiconducting Polymers for Augmenting Biosynthesis and Bioconversion.

Solar-driven biosynthesis and bioconversion are essential for achieving sustainable resources and renewable energy. These processes harness solar energy to produce biomass, chemicals, and fuels. While they offer promising avenues, some challenges and limitations should be investigated and addressed for their improvement and widespread adoption. These include the low utilization of light energy, the inadequate selectivity of products, and the limited utilization of inorganic carbon/nitrogen sources. Organic semiconducting polymers offer a promising solution to these challenges by collaborating with natural microorganisms and developing artificial photosynthetic biohybrid systems. In this Perspective, we highlight the latest advancements in the use of appropriate organic semiconducting polymers to construct artificial photosynthetic biohybrid systems. We focus on how these systems can enhance the natural photosynthetic efficiency of photosynthetic organisms, create artificial photosynthesis capability of nonphotosynthetic organisms, and customize the value-added chemicals of photosynthetic synthesis. By examining the structure-activity relationships and emphasizing the mechanism of electron transfer based on organic semiconducting polymers in artificial photosynthetic biohybrid systems, we aim to shed light on the potential of this novel strategy for artificial photosynthetic biohybrid systems. Notably, these coupling strategies between organic semiconducting polymers and organisms during artificial photosynthetic biohybrid systems will pave the way for a more sustainable future with solar fuels and chemicals.