Analysis of Structural Heterogeneity in Low-Rank Coal and Its Pyrolyzed Char Using Multi-Point Scanning Micro-Raman Spectroscopy.

Understanding the changes in carbon structure during the mid-low-temperature pyrolysis of low-rank coal is important for efficient utilization. Raman spectroscopy is commonly used to analyze the structural order of carbonaceous materials, but traditional methods may overlook the heterogeneity of coal/char. This research explores the heterogeneity of char structure derived from low-rank coal at 700 °C through multi-point micro-Raman analysis. The analysis of parameters such as area (A), intensity (I), full width at half maximum (FWHM/W), and peak position (P) reveals that the carbon structure becomes less ordered as coal transforms into char due to the deposition of small molecules on the surface. The study emphasizes the benefits of multi-point detection for gaining in-depth insights into the structural evolution of carbonaceous materials. The increased standard deviation of Raman parameters indicates diverse structural characteristics resulting from pyrolysis at this temperature, which traditional methods may not capture effectively. The mapping method used in this research visually illustrates the distribution of carbon structures in the region.

Efficient Inhibition of Deep Conversion of Partial Oxidation Products in C-H Bonds' Functionalization Utilizing O2 via Relay Catalysis of Dual Metalloporphyrins on Surface of Hybrid Silica Possessing Capacity for Product Exclusion.

To inhibit the deep conversion of partial oxidation products (POX-products) in C-H bonds' functionalization utilizing O2, 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin cobalt(II) and 5-(4-(chloromethyl)phenyl)-10,15,20-tris(perfluorophenyl)porphyrin copper(II) were immobilized on the surface of hybrid silica to conduct relay catalysis on the surface. Fluorocarbons with low polarity and heterogeneous catalysis were devised to decrease the convenient accessibility of polar POX-products to catalytic centers on the lower polar surface. Relay catalysis between Co and Cu was designed to utilize the oxidation intermediates alkyl hydroperoxides to transform more C-H bonds. Systematic characterizations were conducted to investigate the structure of catalytic materials and confirm their successful syntheses. Applied to C-H bond oxidation, not only deep conversion of POX-products was inhibited but also substrate conversion and POX-product selectivity were improved simultaneously. For cyclohexane oxidation, conversion was improved from 3.87% to 5.27% with selectivity from 84.8% to 92.3%, which was mainly attributed to the relay catalysis on the surface excluding products. The effects of the catalytic materials, product exclusion, relay catalysis, kinetic study, substrate scope, and reaction mechanism were also investigated. To our knowledge, a practical and novel strategy was presented to inhibit the deep conversion of POX-products and to achieve efficient and accurate oxidative functionalization of hydrocarbons. Also, a valuable protocol was provided to avoid over-reaction in other chemical transformations requiring high selectivity.

An artificial intelligence platform for automated PFAS subgroup classification: A discovery tool for PFAS screening.

Since structural analyses and toxicity assessments have not been able to keep up with the discovery of unknown per- and polyfluoroalkyl substances (PFAS), there is an urgent need for effective categorization and grouping of PFAS. In this study, we presented PFAS-Atlas, an artificial intelligence-based platform containing a rule-based automatic classification system and a machine learning-based grouping model. Compared with previously developed classification software, the platform's classification system follows the latest Organization for Economic Co-operation and Development (OECD) definition of PFAS and reduces the number of uncategorized PFAS. In addition, the platform incorporates deep unsupervised learning models to visualize the chemical space of PFAS by clustering similar structures and linking related classes. Through real-world use cases, we demonstrate that PFAS-Atlas can rapidly screen for relationships between chemical structure and persistence, bioaccumulation, or toxicity data for PFAS. The platform can also guide the planning of the PFAS testing strategy by showing which PFAS classes urgently require further attention. Ultimately, the release of PFAS-Atlas will benefit both the PFAS research and regulation communities.

[Influence of Land Use Structure and Spatial Pattern on Water Quality of Small and Medium-sized Rivers in Poyang Lake Basin].

To reveal the influence mechanism of land use structure and spatial pattern on water quality of small and medium-sized rivers, water samples were collected from 25 sampling points in three small and medium-sized rivers of the Poyang Lake Basin in January 2022 and July 2022. Bioenv analysis, the Mantel test, and variance partitioning analysis were used to quantify the effects of land use structure and spatial patterns on water quality at different spatial scales; generalized additive models were used to fit the relationship between water quality and different land use structures and spatial patterns; and a generalized linear model was used to construct segmented regression models and calculate the thresholds based on the stepwise recursive method. The results showed that:① the average interpretation rate of land use structure and spatial pattern on river water quality was 59.72% during the wet period and 48.95% during the dry period. The sub-basin and riparian 100 m scales were the key scales of land use structure and spatial pattern affecting water quality in small and medium-sized rivers, with an average explanation rate of 54.70% and 64.88%, respectively. The joint explanation of land use structure and spatial pattern was an important factor driving the change in river water quality, accounting for 66.90% of the total explanation. ② The impact of land use structure on the water quality of small and medium-sized rivers had a significant threshold effect. When the proportion of construction land was less than 2%, farmland was less than 8%, or forest land was more than 82% at the sub-basin scale and the proportion of construction land was less than 12%, farmland was less than 41%, or forest land was more than 49% at the riparian buffer scale, all could significantly improve water quality. ③ The effect of spatial pattern on water quality in small and medium-sized rivers also had a threshold effect but was weaker than that of land use structure. A patch shape value more than 28.77 or patch diversity more than 0.69 at the sub-basin scale and a patch shape value more than 2.99 or patch diversity more than 1.02 at the riparian buffer scale could improve water quality. The above results showed that strengthening the management of land use at the sub-basin and riparian 100 m scales and setting a reasonable threshold of land use structure and spatial pattern can effectively prevent water quality from deteriorating.

Double boron-oxygen-fused polycyclic aromatic hydrocarbons: skeletal editing and applications as organic optoelectronic materials.

An efficient one-pot strategy for the facile synthesis of double boron-oxygen-fused polycyclic aromatic hydrocarbons (dBO-PAHs) with high regioselectivity and efficient skeletal editing is developed. The boron-oxygen-fused rings exhibit low aromaticity, endowing the polycyclic aromatic hydrocarbons with high chemical and thermal stabilities. The incorporation of the boron-oxygen units enables the polycyclic aromatic hydrocarbons to show single-component, low-temperature ultralong afterglow of up to 20 s. Moreover, the boron-oxygen-fused polycyclic aromatic hydrocarbons can also serve as ideal n-type host materials for high-brightness and high-efficiency deep-blue OLEDs; compared to single host, devices using boron-oxygen-fused polycyclic aromatic hydrocarbons-based co-hosts exhibit dramatically brightness and efficiency enhancements with significantly reduced efficiency roll-offs; device 9 demonstrates a high color-purity (Commission International de l'Eclairage CIEy = 0.104), and also achieves a record-high external quantum efficiency (28.0%) among Pt(II)-based deep-blue OLEDs with Commission International de l'Eclairage CIEy < 0.20; device 10 achieves a maximum brightnessof 27219 cd/m2 with a peak external quantum efficiency of 27.8%, which representes the record-high maximum brightness among Pt(II)-based deep-blue OLEDs. This work demonstrates the great potential of the double boron-oxygen-fused polycyclic aromatic hydrocarbons as ultralong afterglow and n-type host materials in optoelectronic applications.

Stereoselective Sulfa-Michael/Aldol Reaction Promoted by an Axially Chiral Styrene-Based Organocatalyst.

Herein, we describe a stereoselective sulfa-Michael/aldol cyclization reaction promoted by a rationally designed novel axially chiral styrene-based organocatalyst. A variety of highly substituted tetrahydrothiophenes featuring an alkyne-substituted quaternary stereogenic center are obtained in good yields, excellent stereoselectivities, and exclusive trans selectivities. This process tolerates a broad range of alkynyl-substituted acrylamides under mind conditions. The utility of this approach is highlighted in its excellent asymmetric introduction, scalability, and attractive product diversification.

Efficient and Selective Oxygenation of Cycloalkanes and Alkyl Aromatics with Oxygen through Synergistic Catalysis of Bimetallic Active Centers in Two-Dimensional Metal-Organic Frameworks Based on Metalloporphyrins.

Confined catalytic realms and synergistic catalysis sites were constructed using bimetallic active centers in two-dimensional metal-organic frameworks (MOFs) to achieve highly selective oxygenation of cycloalkanes and alkyl aromatics with oxygen towards partly oxygenated products. Every necessary characterization was carried out for all the two-dimensional MOFs. The selective oxygenation of cycloalkanes and alkyl aromatics with oxygen was accomplished with exceptional catalytic performance using two-dimensional MOF Co-TCPPNi as a catalyst. Employing Co-TCPPNi as a catalyst, both the conversion and selectivity were improved for all the hydrocarbons investigated. Less disordered autoxidation at mild conditions, inhibited free-radical diffusion by confined catalytic realms, and synergistic C-H bond oxygenation catalyzed by second metal center Ni employing oxygenation intermediate R-OOH as oxidant were the factors for the satisfying result of Co-TCPPNi as a catalyst. When homogeneous metalloporphyrin T(4-COOCH3)PPCo was replaced by Co-TCPPNi, the conversion in cyclohexane oxygenation was enhanced from 4.4% to 5.6%, and the selectivity of partly oxygenated products increased from 85.4% to 92.9%. The synergistic catalytic mechanisms were studied using EPR research, and a catalysis model was obtained for the oxygenation of C-H bonds with O2. This research offered a novel and essential reference for both the efficient and selective oxygenation of C-H bonds and other key chemical reactions involving free radicals.

Predicting band gaps of MOFs on small data by deep transfer learning with data augmentation strategies.

Porphyrin-based MOFs combine the unique photophysical and electrochemical properties of metalloporphyrins with the catalytic efficiency of MOF materials, making them an important candidate for light energy harvesting and conversion. However, accurate prediction of the band gap of porphyrin-based MOFs is hampered by their complex structure-function relationships. Although machine learning (ML) has performed well in predicting the properties of MOFs with large training datasets, such ML applications become challenging when the training data size of the materials is small. In this study, we first constructed a dataset of 202 porphyrin-based MOFs using DFT computations and increased the training data size using two data augmentation strategies. After that, four state-of-the-art neural network models were pre-trained with the recognized open-source database QMOF and fine-tuned with our augmented self-curated datasets. The GCN models predicted the band gaps of the porphyrin-based materials with the lowest RMSE of 0.2767 eV and MAE of 0.1463 eV. In addition, the data augmentation strategy rotation and mirroring effectively decreased the RMSE by 38.51% and MAE by 50.05%. This study demonstrates that, when proper transfer learning and data augmentation strategies are applied, machine learning models can predict the properties of MOFs using small training data.

Deep transfer learning for predicting frontier orbital energies of organic materials using small data and its application to porphyrin photocatalysts.

Machine learning (ML) models have received increasing attention as a new approach for the virtual screening of organic materials. Although some ML models trained on large databases have achieved high prediction accuracy, the application of ML to certain types of organic materials is limited by the small amount of available data. On the other hand, metalloporphyrins and porphyrins (MpPs) have received increasing attention as potential photocatalysts, and recent studies have found that both HOMO/LUMO energy levels and energy gaps are important factors controlling the MpP photocatalysts. Since the training data of MpPs are insufficient and limited to porphyrin-based dyes, in this study, we proposed a deep transfer learning approach to rapidly predict the HOMO/LUMO energy levels and energy gaps of MpPs. To complement the open-source Porphyrin-based Dyes Database (PBDD), we curated a new database, the Metalloporphyrins and Porphyrins Database (MpPD), in which MpPs were specifically designed as potential photocatalysts and the HOMO/LUMO energies were calculated by advanced DFT functionals. We proposed PorphyBERT, a BERT-based regression model that was pre-trained with PBDD and fine-tuned with MpPD. The model performed satisfactorily in predicting HOMO and LUMO energies and energy gap with RMSEs of 0.0955, 0.0988, and 0.0787 eV and MAEs of 0.0774, 0.0824, and 0.0549 eV. Furthermore, due to its unique unsupervised pre-training phase, the model is not affected by the difference in computational functionals between pre-training and fine-tuning databases. Finally, we recommended 12 MpPs as potential photocatalysts for CO2 reduction with out-of-sample model predictions of energy gaps close to the values calculated by DFT.

Computational Exploration of Dirhodium Complex-Catalyzed Selective Intermolecular Amination of Tertiary vs. Benzylic C-H Bonds.

The mechanism and origins of site-selectivity of Rh2(S-tfpttl)4-catalyzed C(sp3)-H bond aminations were studied using density functional theory (DFT) calculations. The synergistic combination of the dirhodium complex Rh2(S-tfpttl)4 with tert-butylphenol sulfamate TBPhsNH2 composes a pocket that can access both tertiary and benzylic C-H bonds. The nonactivated tertiary C-H bond was selectively aminated in the presence of an electronically activated benzylic C-H bond. Both singlet and triplet energy surfaces were investigated in this study. The computational results suggest that the triplet stepwise pathway is more favorable than the singlet concerted pathway. In the hydrogen atom abstraction by Rh-nitrene species, which is the rate- and site-selectivity-determining step, there is an attractive π-π stacking interaction between the phenyl group of the substrate and the phthalimido group of the ligand in the tertiary C-H activation transition structure. By contrast, such attractive interaction is absent in the benzylic C-H amination transition structure. Therefore, the DFT computational results clearly demonstrate how the synergistic combination of the dirhodium complex with sulfamate overrides the intrinsic preference for benzylic C-H amination to achieve the amination of the nonactivated tertiary C-H bond.

Mechanistic Study of Chemoselectivity for Carbon Radical Hydroxylation versus Chlorination with FeIII (OH)(Cl) Complexes.

The FeIII (OH)(Cl) complex resembles the key intermediate proposed for the non-heme iron halogenases. Goldberg and co-workers reported that the FeIII (OH)(Cl) RC reacts with triphenylmethyl radical 1 to give an exclusive hydroxylation product. To understand the chemoselectivity of the reaction of RC with 1, density functional theory (DFT) calculations have been conducted. From RC, the competing pathways were identified as the OH-transfer, Cl-transfer, and isomerization pathways. The direct Cl-transfer is more favorable than direct OH-transfer by 2.8 kcal/mol. The hydrogen bonding interactions between the hydroxyl group and the pendent amine ligand impede the direct OH-transfer from RC. Compared with the direct Cl-transfer pathway, the isomerization pathways require lower barriers. In isomer RCiso2 , the equatorial hydroxyl group, which has smaller diabatic bond dissociation energy, prefers to transfer to form the hydroxylation product. In FeIII (Cl)2 RC2 and RC2iso , the equatorial chloride group also prefers to transfer to give the chlorination product.

A theoretical study of the ligand-controlled palladium-catalysed regiodivergent synthesis of dibenzosilepin derivatives.

Palladium-catalysed ligand-controlled 1,n-palladium migration of silicon-tethering substrates provides a regiodivergent synthesis strategy for constructing silicon-bridged π-conjugated compounds possessing a 6,6-fused or a 5,7-fused scaffold. Density functional theory (DFT) calculations were carried out to elucidate the detailed mechanism of this 1,n-palladium migration involving syn- or anti-carbopalladation. The computational results suggest that alkyne insertion is the regioselectivity-determining step. Upon catalysis without the BINAP ligand, the 1,2-insertion of an alkyne into the Pd-aryl bond leads to the formation of 6,6-fused benzophenanthrosiline, which is more favorable than the 2,1-insertion of alkyne by 4.2 kcal mol-1. The selective formation of 5,7-fused benzofluorenosilepins via the 2,1-alkyne insertion is facilitated by the BINAP ligand. The 1,2-alkyne insertion with the BINAP ligand is disfavoured due to the steric repulsion between the phenyl group of the substrate and the naphthalene group of the BINAP ligand. The 2,1-alkyne insertion with the BINAP ligand orients the ligand away from the phenyl group of the substrate, which can avoid steric repulsion.

Effect of Water Vapor on Pore Structure, Surface Functional Groups, and Combustion Performance of Pyrolytic Semicoke.

The coal tends to be affected by the water vapor from quenching coke process in the pyrolysis process during the coal carbonization process and in turn causes the variation of physicochemical properties of semicoke. The preparation of semicoke based on different pyrolysis temperatures and water vapor content was carried out in order to investigate the influence of water vaper on physicochemical properties of the pyrolytic semicoke, combined with specific surface area analysis and thermal analysis to study the pore structure and combustion properties of semicoke. The morphology of the semicoke and the alteration rule of carbon-containing functional groups were analyzed by scanning electron microscopy and X-ray photoelectron spectroscopy. The result indicates that adding an appropriate amount of water vapor (40%) instead of excess (60%) in the pyrolysis process (800 °C) is beneficial to the increase of the proportion of fixed carbon and the removal of volatile and ash. The specific surface area and the combustion performance of the semicoke is significantly improved when the appropriate amount of water vapor was added. The water vapor content has a slight effect on surface functional groups when the temperature ranges from 500 to 700 °C, whereas the higher water vapor content inhibits the improvement of physicochemical properties of the semicoke when the pyrolysis temperature is higher (800 °C). Therefore, the entry of excess water vapor (60%) into the high-temperature pyrolysis section should be avoided in the process of quenching coke or it would have an adverse impact on the performance of semicoke.

The efficacy and safety of Longmu Tang granule for the treatment of atopic dermatitis: study protocol for a single-centred, double-blinded, randomised, placebo-controlled trial.

BACKGROUND: Atopic dermatitis (AD) is a chronic relapsing skin disease that has long-term physical and mental health impacts on children with this condition. Current treatments mainly include anti-inflammatory, antibacterial, and anti-allergic interventions, systemic therapy, and recently emerging target-focused agents. However, these treatments have limited effectiveness and unwanted side effects. The use of traditional Chinese medicine (TCM) in the treatment of AD has a long history, with promising efficacies, low toxicity, and improvements in the quality of life of patients with AD. Longmu Tang granule, a TCM, has been used to effectively treat AD since 2008 through doctors' prescriptions. To scientifically evaluate the clinical efficacy and safety of Longmu Tang granule, we proposed to launch a single-centred, double-blinded, randomised, placebo-controlled trial. METHODS: In this single-centred, double-blinded, randomised, placebo-controlled clinical trial conducted at Xiyuan Hospital of China Academy of Chinese Medical Sciences, a total of 60 participants will be randomly assigned (1:1) to receive the Longmu Tang granule or placebo granule for 8 weeks. The primary outcome will be evaluated using the index of Scoring Atopic Dermatitis. The secondary outcomes will be evaluated using the Children's Dermatology Life Quality Index and the number cancellation test. The mechanistic evidence will be the serum levels of inflammatory cytokines, including immunoglobulin E, tumour necrosis factor-α, interleukin-1, and interleukin-6. DISCUSSION: The results of this trial will provide evidence of the efficacy and safety of the Longmu Tang granule and prove its anti-inflammatory action in patients with AD. TRIAL REGISTRATION: Chinese Clinical Trial Registry Chictr.org ID: ChiCTR2100041591 . Registered on 1 January 2021.

A chemometric strategy to automatically screen selected ion monitoring ions for gas chromatography-mass spectrometry-based pseudotargeted metabolomics.

The pseudotargeted metabolomics based on gas chromatography-mass spectrometry (GC-MS) has the advantage of filtering out artifacts originating from sample treatment and accurately quantifying underlying compounds in the analyzed samples. However, this technique faces the problem of selecting high-quality selective ions for performing selected ion monitoring (SIM) on instruments. In this work, we proposed AntDAS-SIMOpt, an automatic untargeted strategy for SIM ion optimization that was accomplished on the basis of an experimental design combined with advanced chemometric algorithms. First, a group of diluted quality control samples was used to screen underlying compounds in samples automatically. Ions in each of the resolved mass spectrum were then evaluated by using the developed algorithms to identify the SIM ion. A Matlab graphical user interface (GUI) was designed to facilitate routine analysis, which can be obtained from http://www.pmdb.org.cn/antdassimopt. The performance of the developed strategy was comprehensively investigated by using standard and complex plant datasets. Results indicated that AntDAS-SIMOpt may be useful for GC-MS-based metabolomics.

Mechanistic Investigation of Palladium-Catalyzed meta-C-H Bond Activation of Arenes with a Carboxyl Directing Group.

The mechanism of Pd(II)-catalyzed meta-C-H bond olefination of arenes with a carboxyl directing group (DG)-containing template has been investigated with density functional theory. The reaction includes three major steps: C-H bond activation, alkene insertion, and ß-hydride elimination. The C-H activation step, which proceeds via a concerted metalation-deprotonation pathway, is found to be the rate- and regioselectivity-determining step. We proposed a mono-N-protected amino acid (MPAA)/DG-assisted C-H activation model, in which the carboxyl DG coordinates with the Pd center and delivers it to the meta-position of arene, and the bidentate dianionic MPAA acts as a base for deprotonation. There is a hydrogen bonding interaction between the carboxyl DG and the carboxylate group of MPAA. An alternative Pd(OAc)2-catalyzed mechanism without involvement of MPAA is also operative. The template is conformationally flexible, and multiple low-energy transition-state conformations contribute to the regioselectivity.

Microwave-assisted Natural Deep Eutectic Solvents Pretreatment Followed by Hydrodistillation Coupled with GC-MS for Analysis of Essential Oil from Turmeric (Curcuma longa L.).

In the past decade, natural deep eutectic solvents (NADESs) as green and sustainable extraction solvents with great potential for the efficient extraction of bioactive compounds from the plants are emerging. In this study, a microwave-assisted technology is used to prepare natural deep eutectic solvents. And natural deep eutectic solvents as pretreatment solvents coupled with microwave-assisted hydrodistillation (MAHD) for isolating essential oil (EO) derived from turmeric (Curcuma longa L.) is investigated. To improve the essential oil yield of turmeric (Curcuma longa L.) as a target, various factors affecting extraction efficiency including the type and amount of natural deep eutectic solvents, pretreatment time, pretreatment temperature and hydrodistillation (HD) time are discussed and optimized through central composite design (CCD) of the response surface methodology (RSM). The optimal conditions are as follows: natural deep eutectic solvent composed of choline chloride and oxalic acid (molar ratio with 1:1) as a pretreatment solvent, an amount of 60 g, a pretreatment time of 5 min, a pretreatment temperature of 84 ºC, a hydrodistillation time of 76 min. Under the optimum conditions, the highest essential oil yield of 0.85% is achieved. Additionally, the essential oil is analyzed by using gas chromatography-mass spectrometry (GC-MS), with a total of 49 compounds being identified. Through combining natural deep eutectic solvents with a microwave-assisted hydrodistillation technique, this work provides an eco-friendly extraction way of isolating essential oil, which boosts development in the monitoring other spice quality field.

Comparison of Early Clinical Results for Femoral Neck System and Cannulated Screws in the Treatment of Unstable Femoral Neck Fractures.

OBJECTIVE: To compare early clinical effects of the femoral neck system (FNS) and three cannulated screws for the treatment of patients with unstable femoral neck fractures. METHODS: A retrospective analysis with pair matching of 81 patients who received FNS or cannulated screw internal fixation for Pauwels type-3 femoral neck fracture in our hospital from January 2019 to December 2019 was conducted. Patients who received FNS were the test group, and those who received cannulated screws comprised the control group. Matching requirements were as follows: same sex, similar age, and similar body mass index (BMI). A total of 30 pairs were successfully matched at a 1:1 ratio, including 12 males and 18 females. The average age of the patients in the FNS group was 54.53 ± 6.71 years. In the cannulated screw group, the average age of the patients was 53.14 ± 7.19 years. The operation time, intraoperative blood loss, hospital stay, hospitalization cost, postoperative visual analog scale (VAS) score, time to walking without crutches, Harris score, femoral head necrosis rate, and complication rate were compared between the groups. RESULTS: Postoperative re-examination of radiographs showed satisfactory reduction in all patients, and all patients were followed up for 10-22 months. Those in the FNS group had lower postoperative VAS scores, earlier times to walking without crutches, higher Harris scores at the last follow-up, and lower complication rates (P < 0.05). VAS scores were lower in the FNS group (3.13 ± 1.07 scores) than in the cannulated screw group (3.77 ± 1.04 scores) (P = 0.018). Patients in the FNS group (5.23 ± 1.33 months) recovered to walking without crutches earlier than did those in the cannulated screw group (6.03 ± 1.45 months) (P<0.001). In addition, a statistically higher postoperative Harris score was detected in the FNS group (86.16 ± 7.26) than in the cannulated screw group (82.37 ± 7.52) (P = 0.039). Overall, a higher incidence of complications was observed in the cannulated screw group (9/30) than in the FNS group (2/30) (P = 0.042). However, intraoperative blood loss and hospitalization costs were greater in the FNS group (P < 0.05). Intraoperative blood loss was greater in the FNS group (99.73 ± 4.69) than in the cannulated screw group (30.27 ± 9.04) (P<0.001). In addition, patients in the FNS group (46976 ± 2270 ¥) spent more on hospitalization costs than did those in the cannulated screw group (15626 ± 1732 ¥) (P<0.001). No statistically significant difference in operation time, hospital stay, or femoral head necrosis rate was observed between the two groups (P > 0.05). CONCLUSION: For patients with unstable femoral neck fractures, FNS has better clinical efficacy than cannulated screws, though it is also more expensive.

Perfluoroalkyl substance pollutants activate the innate immune system through the AIM2 inflammasome.

Perfluoroalkyl substances (PFAS) are widely used in various manufacturing processes. Accumulation of these chemicals has adverse effects on human health, including inflammation in multiple organs, yet how PFAS are sensed by host cells, and how tissue inflammation eventually incurs, is still unclear. Here, we show that the double-stranded DNA receptor AIM2 is able to recognize perfluorooctane sulfonate (PFOS), a common form of PFAS, to trigger IL-1ß secretion and pyroptosis. Mechanistically, PFOS activates the AIM2 inflammasome in a process involving mitochondrial DNA release through the Ca2+-PKC-NF-κB/JNK-BAX/BAK axis. Accordingly, Aim2-/- mice have reduced PFOS-induced inflammation, as well as tissue damage in the lungs, livers, and kidneys in both their basic condition and in an asthmatic exacerbation model. Our results thus suggest a function of AIM2 in PFOS-mediated tissue inflammation, and identify AIM2 as a major pattern recognition receptor in response to the environmental organic pollutants.