Your personal choices in transportation and food are important for lowering carbon emissions

There is a global need to reduce greenhouse gas emissions to limit the extent of climate change.A better understanding of how our own activities and lifestyle influence our energy use and carbon emissions can help us enable changes in activities that can lead to reductions in carbon emissions.Here we discuss an approach based on examining carbon emissions from the perspective of the unit C,where 1 C is the CO_(2)from food a person would on average eat every day.This approach shows that total CO_(2)emissions in China,normalized by the population,is 22.5 C while carbon emissions for a person in the US is 43.9 C.A better appreciation of our own energy use can be obtained by calculating carbon emissions from our own activities in units of C,for example for driving a car gasoline or electric vehicle a certain number of kilometers,using electricity for our homes,and eating different foods.With this information,we can see how our carbon emissions compare to national averages in different countries and make decisions that could lower our personal CO_(2)emissions.

Data-driven interpretable analysis for polysaccharide yield prediction

Cornstalks show promise as a raw material for polysaccharide production through xylanase.Rapid and accurate prediction of polysaccharide yield can facilitate process optimization,eliminating the need for extensive experimentation in actual production to refine reaction conditions,thereby saving time and costs.However,the intricate interplay of enzymatic factors poses challenges in predicting and optimizing polysaccharide yield accurately.Here,we introduce an innovative data-driven approach leveraging multiple artificial intelligence techniques to enhance polysaccharide production.We propose a machine learning framework to identify highly accurate polysaccharide yield prediction modeling methods and uncover optimal enzymatic parameter combinations.Notably,Random Forest(RF)and eXtreme Gradient Boost(XGB)demonstrate robust performance,achieving prediction accuracies of 93.0%and 95.6%,respectively,while an independently developed deep neural network(DNN)model achieves 91.1%accuracy.A feature importance analysis of XGB reveals the enzyme solution volume's dominant role(43.7%),followed by time(20.7%),substrate concentration(15%),temperature(15%),and pH(5.6%).Further interpretability analysis unveils complex parameter interactions and potential optimization strategies.This data-driven approach,incorporating machine learning,deep learning,and interpretable analysis,offers a viable pathway for polysaccharide yield prediction and the potential recovery of various agricultural residues.

Cathodic biofouling control by microbial separators in air-breathing microbial fuel cells

Microbial fuel cells(MFCs)incorporating air-breathing cathodes have emerged as a promising ecofriendly wastewater treatment technology capable of operating on an energy-free basis.However,the inevitable biofouling of these devices rapidly decreases cathodic catalytic activity and also reduces the stability of MFCs during long-term operation.The present work developed a novel microbial separator for use in air-breathing MFCs that protects cathodic catalytic activity.In these modified devices,microbes preferentially grow on the microbial separator rather than the cathodic surface such that biofouling is prevented.Trials showed that this concept provided low charge transfer and mass diffusion resistance values during the cathodic oxygen reduction reaction of 4.6±1.3 and 17.3±6.8 U,respectively,after prolonged operation.The maximum power density was found to be stable at 1.06±0.07 W m
2 throughout a long-term test and the chemical oxygen demand removal efficiency was increased to 92%compared with a value of 83%for MFCs exhibiting serious biofouling.In addition,a cathode combined with a microbial separator demonstrated less cross-cathode diffusion of oxygen to the anolyte.This effect indirectly induced the growth of electroactive bacteria and produced higher currents in air-breathing MFCs.Most importantly,the present microbial separator concept enhances both the lifespan and economics of air-breathing MFCs by removing the need to replace or regenerate the cathode during longterm operation.These results indicate that the installation of a microbial separator is an effective means of stabilizing power generation and ensuring the cost-effective performance of air-breathing MFCs intended for future industrial applications.

HMGB3 is a potential diagnostic marker for early cervical lesion screening

Despite the spread of effective vaccination strategies,cervical cancer remains the second leading cause of cancer death among women aged 20 to 39.1 clinical diagnosis of cervical lesions relies on the P16INK4a(P16)marker,but its sensitivity to low-grade cervical intraepithelial neoplasia(CIN)is limited.Exploring more sensitive and specific molecular markers is still a challenge in cervical lesion screening.In this study,we found that HMGB3 could effectively label pathological cells in different cervical lesions,especially for early CIN.Therefore,HMGB3 has the potential to be used as a novel marker for the early screening of cervical lesions.

Nanofiltration for drinking water treatment: a review

In recent decades,nanofiltration(NF)is considered as a promising separation technique to produce drinking water from different types of water source.In this paper,we comprehensively reviewed the progress of NFbased drinking water treatment,through summarizing the development of materials/fabrication and applications of NF membranes in various scenarios including surface water treatment,groundwater treatment,water reuse,brackish water treatment,and point of use applications.We not only summarized the removal of target major pollutants(e.g.,hardness,pathogen,and natural organic matter),but also paid attention to the removal of micropollutants of major concern(e.g.,disinfection byproducts,per-and polyfluoroalkyl substances,and arsenic).We highlighted that,for different applications,fit-for-purpose design is needed to improve the separation capability for target compounds of NF membranes in addition to their removal of salts.Outlook and perspectives on membrane fouling control,chlorine resistance,integrity,and selectivity are also discussed to provide potential insights for future development of high-efficiency NF membranes for stable and reliable drinking water treatment.

Asymmetric synthesis of pyrrolo[1,2-a]indoles via organocatalytic[3+2]annulation of substituted 2-vinylindoles with azlactones

The chiral phosphoric acid catalyzed asymmetric[3+2]annulation of substituted 2-vinylindoles with azlactones has been established.This reaction represented a practical approach for the synthesis of structurally diverse pyrrolo[1,2-a]indoles with two vicinal stereocenters including one tetrasubstituted stereocenter in good yields and good stereoselectivities under mild conditions.

Organocatalytic asymmetric [3+3] annulation of isatin N,N’-cyclic azomethine imines with enals:Efficient approach to functionalized spiro N-heterocyclic oxindoles

An unprecedented chiral secondary amine-catalyzed [3+3] annulation of isatin N,N’-cyclic azomethine imines with α,β-unsaturated aldehydes was developed.This strategy allowed the construction of structurally novel spiro N-heterocyclic oxindole derivatives in good yields(up to 91%) and good to excellent enantioselectivities(up to>99% ee),albeit with modest diastereoselectivities(up to 3.1:1 dr).

Diastereoselective synthesis of functionalized tetrahydro-γ-carbolines via a[3+3] cycloaddition of 2,2’-diester aziridines with β-(indol-2-yl)-α,β-unsaturated ketones

A Sc(OTf)3-catalyzed[3+3]cycloaddition of 2,2’-diester aziridines withβ-(indol-2-yl)-α,β-unsaturated ketones was developed,affording polysubstituted tetrahydro-y-carbolines in single diastereoisomers in good to excellent yields.

Characterization of amyloid-β precursor protein intracellular domain-associated transcriptional complexes in SH-SY5Y neurocytes

Objective Alzheimer＇s disease （AD） is one of the major disorders worldwide. Recent research suggests that the amyloid-β precursor protein intracellular domain （AICD） is a potential contributor to AD development and progression. The small AICD is rapidly degraded after processing from the full-length protein. The present study aimed to apply a highly efficient biotinylation approach in vitro to study AICD-associated complexes in neurocytes. Methods By coexpressing Escherichia coli biotin ligase with biotinyl-tagged AICD in the SH-SY5Y neuronal cell line, the effects of AICD overexpression on cell proliferation and apoptosis were analyzed. Besides, AICD-associated nuclear transcriptional complexes were purified and then examined by mass spectrometry. Results Our data showed that AICD overexpression not only affected cell proliferation but also led to apoptosis in differentiated SH-SY5Y cells. Moreover, biotinylation allowed single-step purification of biotinylated AICD-associated complexes from total nuclear extract via high-affinity biotin-streptavidin binding. Following this by mass spectrometry, we identified physically associated proteins, some reported previously and other novel binding partners, CUX1 and SPT5. Conclusion Based on these results, a map of the AICD-associated nuclear interactome was depicted. Specifically, AICD can activate CUX1 transcriptional activity, which may be associated with AICD-dependent neuronal cell death. This work helps to understand the AICD-associated biological events in AD progression and provides novel insights into the development of AD.