AttABseq: an attention-based deep learning prediction method for antigen-antibody binding affinity changes based on protein sequences.

The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods have been actively developed to accelerate and improve the development of therapeutic antibodies. In this study, we developed an end-to-end sequence-based deep learning model, termed AttABseq, for the predictions of the antigen-antibody binding affinity changes connected with antibody mutations. AttABseq is a highly efficient and generic attention-based model by utilizing diverse antigen-antibody complex sequences as the input to predict the binding affinity changes of residue mutations. The assessment on the three benchmark datasets illustrates that AttABseq is 120% more accurate than other sequence-based models in terms of the Pearson correlation coefficient between the predicted and experimental binding affinity changes. Moreover, AttABseq also either outperforms or competes favorably with the structure-based approaches. Furthermore, AttABseq consistently demonstrates robust predictive capabilities across a diverse array of conditions, underscoring its remarkable capacity for generalization across a wide spectrum of antigen-antibody complexes. It imposes no constraints on the quantity of altered residues, rendering it particularly applicable in scenarios where crystallographic structures remain unavailable. The attention-based interpretability analysis indicates that the causal effects of point mutations on antibody-antigen binding affinity changes can be visualized at the residue level, which might assist automated antibody sequence optimization. We believe that AttABseq provides a fiercely competitive answer to therapeutic antibody optimization.

ML-PLIC: a web platform for characterizing protein-ligand interactions and developing machine learning-based scoring functions.

Cracking the entangling code of protein-ligand interaction (PLI) is of great importance to structure-based drug design and discovery. Different physical and biochemical representations can be used to describe PLI such as energy terms and interaction fingerprints, which can be analyzed by machine learning (ML) algorithms to create ML-based scoring functions (MLSFs). Here, we propose the ML-based PLI capturer (ML-PLIC), a web platform that automatically characterizes PLI and generates MLSFs to identify the potential binders of a specific protein target through virtual screening (VS). ML-PLIC comprises five modules, including Docking for ligand docking, Descriptors for PLI generation, Modeling for MLSF training, Screening for VS and Pipeline for the integration of the aforementioned functions. We validated the MLSFs constructed by ML-PLIC in three benchmark datasets (Directory of Useful Decoys-Enhanced, Active as Decoys and TocoDecoy), demonstrating accuracy outperforming traditional docking tools and competitive performance to the deep learning-based SF, and provided a case study of the Serine/threonine-protein kinase WEE1 in which MLSFs were developed by using the ML-based VS pipeline in ML-PLIC. Underpinning the latest version of ML-PLIC is a powerful platform that incorporates physical and biological knowledge about PLI, leveraging PLI characterization and MLSF generation into the design of structure-based VS pipeline. The ML-PLIC web platform is now freely available at http://cadd.zju.edu.cn/plic/.

Comprehensive assessment of protein loop modeling programs on large-scale datasets: prediction accuracy and efficiency.

Protein loops play a critical role in the dynamics of proteins and are essential for numerous biological functions, and various computational approaches to loop modeling have been proposed over the past decades. However, a comprehensive understanding of the strengths and weaknesses of each method is lacking. In this work, we constructed two high-quality datasets (i.e. the General dataset and the CASP dataset) and systematically evaluated the accuracy and efficiency of 13 commonly used loop modeling approaches from the perspective of loop lengths, protein classes and residue types. The results indicate that the knowledge-based method FREAD generally outperforms the other tested programs in most cases, but encountered challenges when predicting loops longer than 15 and 30 residues on the CASP and General datasets, respectively. The ab initio method Rosetta NGK demonstrated exceptional modeling accuracy for short loops with four to eight residues and achieved the highest success rate on the CASP dataset. The well-known AlphaFold2 and RoseTTAFold require more resources for better performance, but they exhibit promise for predicting loops longer than 16 and 30 residues in the CASP and General datasets. These observations can provide valuable insights for selecting suitable methods for specific loop modeling tasks and contribute to future advancements in the field.

Glyceryl triacetate promotes blood-brain barrier recovery after ischemic stroke through lipogenesis-mediated IL-33 in mice.

BACKGROUND: Lipid metabolism has a crucial role in neural repair in neurodegenerative diseases. We recently revealed that lipogenesis-mediated interleukin-33 (IL-33) upregulation lead to blood-brain barrier (BBB) repair after ischemic stroke. However, manipulating the key enzyme fatty acid synthase (FASN) to enhance lipogenesis was very challenging. Glyceryl triacetate (GTA) was used as a donor of acetate and precursor of acetyl coenzyme A, the key substrate for de novo lipogenesis catalyzed by FASN. Therefore, we hypothesized that GTA would promote lipogenesis the peri-infarct after ischemic stroke and contribute to the BBB repair through IL-33. METHODS: Middle cerebral artery occlusion (MCAO) was performed on C57BL mice and GTA was gavage administrated (4 g/kg) on day 2 and 4 after MCAO. Lipogenesis was evaluated by assessment of the protein level of FASN, lipid droplets, and fatty acid products through liquid chromatography-mass spectrometry in the peri-infarct area on day 3 after MCAO, respectively. BBB permeability was determined by extravasation of Evans blue, IgG and dextran, and levels of tight junction proteins in the peri-infarct area on day 7 after MCAO, respectively. Infarct size and neurological defects were assessed on day 7 after MCAO. Brain atrophy on day 30 and long-term sensorimotor abilities after MCAO were analyzed as well. The inhibitor of FASN, C75 and the virus-delivered FASN shRNA were used to evaluate the role of FASN-driven lipogenesis in GTA-improved BBB repair. Finally, the therapeutic potential of recombinant IL-33 on BBB repair and neurological recovery was evaluated. RESULTS: We found that treatment with GTA increased the lipogenesis as evidenced by lipid droplets level and lauric acid content, but not the FASN protein level. Treatment with GTA increased the IL-33 level in the peri-infarct area and decreased the BBB permeability after MCAO. However, infarct size and neurological defect score were unchanged on day 7 after MCAO, while the long-term recovery of sensorimotor function and brain atrophy were improved by GTA. Inhibition of lipogenesis using C75 or FASN shRNA reversed the beneficial effect of GTA. Finally, exogenous IL-33 improved BBB repair and long-term functional recovery after stroke. CONCLUSION: Collectively, we concluded that treatment with GTA improved the BBB repair and functional recovery after ischemic stroke, probably by the enhancement of lipogenesis and IL-33 expression.

AI-algorithm-assisted 895-nm praseodymium laser emitting sub-100-fs pulses.

Praseodymium (Pr) lasers have achieved outstanding pico- and sub-picosecond pulsations covering the near-infrared (NIR) and visible spectral range in recent years. However, it has been a stagnant task for more than two decades to leapfrog into the sub-100 femtosecond (fs) regime as the Pr gain bandwidths are too narrow for their major transition lines. Although the wide tunability at the NIR bands in the Pr:YLF crystals has been explored, the spectral tails in these transitions suffer severely from weak gains for mode locking, combined with the intricate dispersion control to achieve transform-limit formation. In this work, we target the Pr:YLF's 895-nm line with a specially designed edge-pass filter to balance the gain bandwidth and transitional strength. By deploying a symmetric dispersion scheme and tuning with the soft actor-critic artificial intelligence (AI) algorithm, we have achieved the pulse duration down to sub-100-fs in a Pr laser for the first time. This work also enriches the AI-assisted methodology for ultrafast solid-state laser realizations.

Association of cesarean section with asthma in children/adolescents: a systematic review and meta-analysis based on cohort studies.

BACKGROUND: Whether cesarean section (CS) is a risk factor for asthma in offspring is controversial. The purpose of this study was to investigate the association between CS and asthma in children/adolescents. METHODS: Pubmed, Embase, Web of Science, and Cochrane Library electronic databases were searched for cohort studies on the relationship between mode of delivery and asthma in children/adolescents up to February 2023. Birth via CS was considered an exposure factor. Asthma incidence was taken as a result. RESULTS: Thirty-five cohort studies (thirteen prospective and twenty-two retrospective cohort studies) were included. The results showed that the incidence of asthma was higher in CS offspring (odds ratio (OR) = 1.18, P < 0.001) than in the vaginal delivery (VD) group. Partial subgroup analyses showed a higher incidence of asthma in female offspring born via CS (OR = 1.26, P < 0.001) compared with the VD group, while there was no difference in males (OR = 1.07, P = 0.325). Asthma incidence was higher in CS offspring than in the VD group in Europe (OR = 1.20, P < 0.001), North America (OR = 1.15, P < 0.001), and Oceania (OR = 1.06, P = 0.008). This trend was not found in the Asian population (OR = 1.17, P = 0.102). The incidence of atopic asthma was higher in offspring born via CS (OR = 1.14, P < 0.001) compared to the VD group. The CS group had a higher incidence of persistent asthma, but the difference did not reach statistical significance (OR = 1.15, P = 0.063). CONCLUSION: In this meta-analysis, CS may be a risk factor for asthma in offspring children/adolescents compared with VD. The relationship between CS and asthma was influenced by sex and region.

Metformin attenuates sevoflurane-induced neurogenesis damage and cognitive impairment: involvement of the Nrf2/G6PD pathway.

Anesthetics such as sevoflurane are commonly administered to infants and children. However, the possible neurotoxicity caused by prolonged or repetitive exposure to it should be a concern. The neuroprotective effects of metformin are observed in many models of neurological disorders. In this study, we investigated whether metformin could reduce the developmental neurotoxicity induced by sevoflurane exposure in neonatal rats and the potential mechanism. Postnatal day 7 (PND 7) Sprague-Dawley rats and neural stem cells (NSCs) were treated with normal saline or metformin before sevoflurane exposure. The Morris water maze (MWM) was used to observe spatial memory and learning at PND 35-42. Immunofluorescence staining was used to detect neurogenesis in the subventricular zone (SVZ) of the lateral ventricle and the subgranular zone (SGZ) of the dentate gyrus at PND 14. MTT assays, immunofluorescence staining, and TUNEL staining were used to assess the viability, proliferation, differentiation, and apoptosis of NSCs. Western blotting and ELISA were used to assess the protein expression of cleaved caspase-3, nuclear factor erythroid 2-related factor 2 (Nrf2), and glucose-6-phosphate dehydrogenase (G6PD) pathway-related molecules. Exposure to sevoflurane resulted in late cognitive defects, impaired neurogenesis in both the SVZ and SGZ, reduced NSC viability and proliferation, increased NSC apoptosis, and decreased protein expression of G6PD in vitro. Metformin pretreatment attenuated sevoflurane-induced cognitive functional decline and neurogenesis inhibition. Metformin pretreatment also increased the protein expression of Nrf2 and G6PD. However, treatment with the Nrf2 inhibitor, ML385 or the G6PD inhibitor, dehydroepiandrosterone (DHEA) reversed the protective effect of metformin on sevoflurane-induced NSC damage in vitro. Our findings suggested that metformin could reduce sevoflurane-induced neurogenesis damage and neurocognitive defects in the developing rat brain by influencing the Nrf2/G6PD signaling pathways.

Enhanced Charge Separation for Efficient Photocatalytic H2 Production by Long-Lived Trap-State-Induced Interfacial Charge Transfer.

Photogeneration of charge carriers in semiconductors provides the scientific fundamental for photocatalytic water splitting. However, an ongoing challenge is the development of a new mechanism promoting charge carrier separation. Here we propose a trap-state-induced interfacial charge-transfer transition mechanism (TSICTT), in which electrons in long-lived trap states recombine with holes on the valence band (VB) of the semiconductor, thus prolonging the electron lifetime. We demonstrate this concept in the Sr4Al14O25:Eu2+, Dy3+/CdS (SAO/CdS) heterostructure, where trapped electrons with a lifetime of up to several hours in the SAO persistent luminescence phosphor (PLP) can continuously consume holes on the VB of CdS nanoparticles (NPs). We discover that the interfacial interaction and the work function difference between SAO and CdS are crucial for the TSICTT, which finally contributes to the improved H2 production from 34.4 to 1212.9 µmol gCdS-1 h-1 under visible-light irradiation. This model introduces a new strategy to manipulate charge carrier transport for the effective utilization of solar energy.

Highly efficient near-infrared light-emitting diodes based on Zn:CuInSe2/ZnS//ZnS quantum dots with double shell engineering.

Near-infrared (NIR) quantum dot-based light-emitting diodes (QLEDs) developed rapidly in the fields of biomedical applications, telecommunications, sensing and diagnostics. However, it remains an enormous challenge for the synthesis of high-quality NIR QD materials with low toxicity or non-toxicity, high photoluminescence (PL) quantum yields (QYs) and high stability. Herein, we used a facile method to synthesize large-sized (8 nm) and thick-shell NIR Zn:CuInSe2/ZnS//ZnS QDs by engineering a double ZnS shell. The resulting NIR QDs exhibited high PL QYs of 80%, and excellent photochemical stability, which could be ascribed to the decreased lattice mismatch of the core/shell interface by the introduced Zn element into CuInSe2 cores and the energetic defect passivation of the double ZnS shell engineering. Furthermore, the high-quality Zn:CuInSe2/ZnS//ZnS QDs based LEDs exhibited the maximum external quantum efficiency (EQE) of 3.0%, 4.0% and 2.5% for PL peaks located at 705, 719 and 728 nm, respectively. This efficiency is comparable to that of the outstanding PbS- and InAs-based NIR QLEDs, as well as the avoidance of toxic heavymetal and/or hazardous reagents in this work. The synthesized high-quality Zn:CuInSe2/ZnS//ZnS QDs could be expected to promote the potential applications of heavy-metal-free QDs in the NIR fields.

Progressive gray matter hypertrophy with severity stages of insomnia disorder and its relevance for mood symptoms.

OBJECTIVE: To investigate the gray matter (GM) alterations in patients with insomnia disorder (ID) at different severity stages and the relationship between GM alterations and sleep, mood, and cognitive measures. METHODS: One hundred one ID patients and 63 healthy controls (HC) were included. Each patient underwent structural MRI and completed sleep-, mood-, and cognitive-related questionnaires. The ID patients were further grouped into subthreshold insomnia (SI) group and clinical insomnia (CI) group. We investigated changes in GM volumes in ID patients via diffeomorphic anatomical registration through exponentiated lie algebra voxel-based morphometry (DARTEL-VBM). We first compared voxel-wise differences in GM volumes between the HC group and the ID group. Analysis of variance was performed on individual GM maps in the SI, CI, and HC groups to further investigate the effects of different stages of ID severity on GM volumes. Multiple regression was used to model the relationship between altered GM volumes in SI and CI groups and clinical measures. RESULTS: GM hypertrophies in the left anterior and middle cingulate gyrus, right middle and inferior temporal gyrus, and right cerebellum Crus II were detected in ID. Increased GM volume in the right middle temporal gyrus was detected in the SI group, whereas all three regions in the CI group. Regression analysis showed that mood- and cognitive-related measures had a positive correlation with GM volumes, while sleep-related measures had a negative correlation with GM volumes in the CI group. CONCLUSIONS: Our findings of the progressively increased GM volumes in ID suggest that a hypertrophic cortical morphological mechanism may underlie the altered neuroanatomy induced by insomnia. KEY POINTS: • Insomnia-induced GM hypertrophies in the cingulate gyrus, temporal gyrus, and cerebellum Crus II. • The middle temporal gyrus was early detectable in the SI group. • The increased GM volumes in the CI group were correlated with clinical measures.

Altered resting state connectivity in right side frontoparietal network in primary insomnia patients.

OBJECTIVE: This study investigated alterations of resting-state networks (RSNs) in primary insomnia patients as well as relationships between these changes and clinical features. METHODS: Fifty-nine primary insomnia patients and 53 healthy control subjects underwent a resting-state fMRI scan (rs-fMRI). Ten RSNs were identified using independent component analysis of rs-fMRI data. To assess significant differences between the two groups, voxel-wise analysis of ten RSNs was conducted using dual regression with FSL randomised non-parametric permutation testing and a threshold-free cluster enhanced technique to control for multiple comparisons. Relationships between abnormal functional connectivity and clinical variables were then investigated with Pearson's correlation analysis. RESULTS: Primary insomnia patients showed decreased connectivity in regions of the right frontoparietal network (FPN), including the superior parietal lobule and superior frontal gyrus. Moreover, decreased connectivity in the right middle temporal gyrus and right lateral occipital cortex with the FPN showed significant positive correlations with disease duration and self-rated anxiety, respectively. CONCLUSIONS: Our study suggests that primary insomnia patients are characterised by abnormal organisation of the right FPN, and dysfunction of the FPN is correlated with disease duration and anxiety. The results enhance our understanding of neural substrates underlying symptoms of primary insomnia from the viewpoint of resting-state networks. KEY POINTS: • Primary insomnia patients showed altered functional connectivity in the right FPN. • Middle temporal gyrus FC with FPN was significantly correlated with disease duration. • Lateral occipital cortex FC with FPN was significantly correlated with SAS scores.

Increased insular connectivity with emotional regions in primary insomnia patients: a resting-state fMRI study.

OBJECTIVE: To explore the abnormal connectivity patterns between the insular and the voxels of the brain in primary insomnia (PI) with insular-based functional connectivity (FC). METHODS: With the resting-state fMRI data acquired from 57 PI patients and 46 healthy controls, a two-sample t test was performed on individual FC correlation maps from two groups. The person correlation analysis was used to evaluate the relationship between the abnormal FC and clinical features. RESULTS: PI patients show enhanced connectivity between the left insula with the right anterior cingulate cortex (p < 0.05 and p < 0.001, AlphaSim-corrected), right frontal sup orb, bilateral thalamus and left precuneus,as well as decreased connectivity with the left middle temporal gyrus and right fusiform (p < 0.05, AlphaSim-corrected). Correlation analysis indicated the enhanced connectivities in the PI patients have significant negative correlations with Self-Rating Depression Scale(SDS)and Self-Rating Anxiety Scale(SAS)scores. In addition, the decreased functional connectivities showed positive correlations with SDS and SAS scores. CONCLUSION: Our study showed the increased connectivity regions with insula were mainly in the emotional circle and decreased connectivity was in cognitive-related regions. These provide additional evidence from functional integration view to understand the possible underlying neural- mechanisms of PI. KEY POINTS: • The aberrant insular-based connectivity pattern of PI patients was detected. • Regions showing increased connectivity with left insular were mainly in emotional circle. • Significant correlations between changed FC and SDS and SAS score were found.

Adsorptive removal of antibiotics from water using magnetic ion exchange resin.

The occurrence of antibiotics in the environment has recently raised serious concern regarding their potential threat to aquatic ecosystem and human health. In this study, the magnetic ion exchange (MIEX) resin was applied for removing three commonly-used antibiotics, sulfamethoxazole (SMX), tetracycline (TCN) and amoxicillin (AMX) from water. The results of batch experiments show that the maximum adsorption capacities on the MIEX resin for SMX, TCN and AMX were 789.32, 443.18 and 155.15µg/mL at 25°C, respectively, which were 2-7 times that for the powdered activated carbon. The adsorption kinetics of antibiotics on the MIEX resin could be simulated by the pseudo-second-order model (R2=0.99), and the adsorption isotherm data were well described by the Langmuir model (R2=0.97). Solution pH exhibited a remarkable impact on the adsorption process and the absorbed concentrations of the tested antibiotics were obtained around the neutral pH. The MIEX resin could be easily regenerated by 2mol/L NaCl solution and maintained high adsorption removal for the tested antibiotics after regeneration. Anion exchange mechanism mainly controlled the adsorption of antibiotic and the formation of hydrogen binding between the antibiotic and resin can also result in the increase of adsorption capacity. The high adsorption capacity, fast adsorption rate and prominent reusability make the MIEX resin a potential adsorbent in the application for removing antibiotics from water.

Reduced Integrity of Right Lateralized White Matter in Patients with Primary Insomnia: A Diffusion-Tensor Imaging Study.

Purpose To analyze the integrity of white matter (WM) tracts in primary insomnia patients and provide better characterization of abnormal WM integrity and its relationship with disease duration and clinical features of primary insomnia. Materials and Methods This prospective study was approved by the ethics committee of the Guangdong No. 2 Provincial People's Hospital. Tract-based spatial statistics were used to compare changes in diffusion parameters of WM tracts from 23 primary insomnia patients and 30 healthy control (HC) participants, and the accuracy of these changes in distinguishing insomnia patients from HC participants was evaluated. Voxel-wise statistics across subjects was performed by using a 5000-permutation set with family-wise error correction (family-wise error, P < .05). Multiple regressions were used to analyze the associations between the abnormal fractional anisotropy (FA) in WM with disease duration, Pittsburgh Sleep Quality Index, insomnia severity index, self-rating anxiety scale, and the self-rating depression scale in primary insomnia. Characteristics for abnormal WM were also investigated in tract-level analyses. Results Primary insomnia patients had lower FA values mainly in the right anterior limb of the internal capsule, right posterior limb of the internal capsule, right anterior corona radiata, right superior corona radiata, right superior longitudinal fasciculus, body of the corpus callosum, and right thalamus (P < .05, family-wise error correction). The receiver operating characteristic areas for the seven regions were acceptable (range, 0.60-0.74; 60%-74%). Multiple regression models showed abnormal FA values in the thalamus and body corpus callosum were associated with the disease duration, self-rating depression scale, and Pittsburgh Sleep Quality Index scores. Tract-level analysis suggested that the reduced FA values might be related to greater radial diffusivity. Conclusion This study showed that WM tracts related to regulation of sleep and wakefulness, and limbic cognitive and sensorimotor regions, are disrupted in the right brain in patients with primary insomnia. The reduced integrity of these WM tracts may be because of loss of myelination. (©) RSNA, 2016.

Regional homogeneity changes in patients with primary insomnia.

PURPOSE: The study aimed to explore the regional spontaneous activity changes in primary insomnia (PI) patients. MATERIALS AND METHODS: Based on the resting-state fMRI datasets acquired from 59 PI patients and 47 healthy controls, a two-sample t-test was performed on individual normalized regional homogeneity (ReHo) maps. Relationships between abnormal ReHo values and the Pittsburgh Sleep Quality Index (PSQI), the self-rating anxiety scale (SAS) and the self-rating depression scale (SDS) were investigated with Pearson correlation analysis. RESULTS: In PI patients, we found increased ReHo in the left insula, right anterior cingulate gyrus, bilateral precentral gyrus and left cuneus, as well as decreased ReHo in the right middle cingulate cortex and left fusiform (p < 0.05, AlphaSim-corrected). We also found a significant positive correlation between increased ReHo in the left insula and SAS scores, decreased ReHo in the right middle cingulated cortex and SDS, SAS scores as well as a negative correlation between increased ReHo in the right precentral gyrus and SDS scores (p < 0.05). CONCLUSIONS: Our study found abnormal spontaneous activities in multiple brain regions, especially in emotion-related areas in PI patients. Alterative activities in these regions might contribute to an understanding the intrinsic functional architecture of insomnia and its clinical features. KEY POINTS: • Regional spontaneous activity changes were detected in PI patients. • Decreased or increased ReHo of some regions was identified in PI patients. • Significant correlations between mean ReHo and SDS scores were found.

Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis.

Neuroimaging studies suggested that drug addiction is linked to abnormal brain functional connectivity. However, little is known about the alteration of brain white matter (WM) connectivity in addictive drug users and nearly no study has been performed to examine the alterations of brain WM connectivity in heroin-dependent individuals (HDIs). Diffusion tensor imaging (DTI) offers a comprehensive technique to map the whole brain WM connectivity in vivo. In this study, we acquired DTI datasets from 20 HDIs and 18 healthy controls and constructed their brain WM structural networks using a deterministic fibre tracking approach. Using graph theoretical analysis, we explored the global and nodal topological parameters of brain network for both groups and adopted a network-based statistic (NBS) approach to assess between-group differences in inter-regional WM connections. Statistical analysis indicated the global efficiency and network strength were significantly increased, but the characteristic path length was significantly decreased in the HDIs compared with the controls. We also found that in the HDIs, the nodal efficiency was significantly increased in the left prefrontal cortex, bilateral orbital frontal cortices and left anterior cingulate gyrus. Moreover, the NBS analysis revealed that in the HDIs, the significant increased connections were located in the paralimbic, orbitofrontal, prefrontal and temporal regions. Our results may reflect the disruption of whole brain WM structural networks in the HDIs. Our findings suggest that mapping brain WM structural network may be helpful for better understanding the neuromechanism of heroin addiction.

[Diagnostic values of fractional exhaled nitric oxide for typical bronchial asthma and cough variant asthma in children].

OBJECTIVE: To study the diagnostic values of fractional exhaled nitric oxide (FeNO) for typical bronchial asthma and cough variant asthma in children, and to explore whether FeNO can be applied to differentiate typical bronchial asthma from cough variant asthma in children. METHODS: A total of 150 children who were newly diagnosed with typical bronchial asthma between June 2012 and June 2014, as well as 120 children who were newly diagnosed with cough variant asthma during the same period, were selected as subjects. FeNO measurement, spirometry, and methacholine provocation test were performed for both groups. Meanwhile, 150 healthy children were selected as the control group, and their FeNO was measured. The diagnostic values of FeNO for typical bronchial asthma and cough variant asthma were analyzed using the receiver operating characteristic curve. RESULTS: The FeNO values in the typical bronchial asthma and cough variant asthma groups were significantly higher than in the control group (P<0.01), and the FeNO value in the typical bronchial asthma group was significantly higher than in the cough variant asthma group (P<0.01). FEV1/FVC%, FEV1%pred, and PD20 were significantly lower in the typical bronchial asthma group than in the cough variant asthma group (P<0.01). The optimal cut-off value of FeNO was 19.5 ppb for the diagnosis of typical bronchial asthma, with a sensitivity of 83.3% and a specificity of 86.7%; the optimal cut-off value of FeNO was 15.5 ppb for the diagnosis of cough variant asthma, with a sensitivity of 67.5% and a specificity of 78.0%; the optimal cut-off value of FeNO was 28.5 ppb for the differentiation between typical bronchial asthma and cough variant asthma, with a sensitivity of 60.7% and a specificity of 82.5%. CONCLUSIONS: Measurenment of FeNO may be useful in the diagnosis and differential diagnosis of typical bronchial asthma and cough variant asthma.

The potential mechanism of Guizhi Fuling Wan effect in the treatment of cervical squamous cell carcinoma: A bioinformatics analysis investigation.

As a global malignancy with high mortality rate, targeted drug development for Uterine Cervical Neoplasms is an important direction. The traditional formula Guizhi Fuling Wan (GFW) is widely used in gynecological diseases. However, its potential mechanism of action remains to be discovered. We retrieved GFW and cervical squamous cell carcinoma (CSCC) targets from public databases. The protein-protein interaction network was obtained by string computational analysis and imported Cytoscape_v3.9.0 to obtain the core network and the top 10 Hub genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used for enrichment analysis of the core network, and then molecular docking to verify whether the selected signaling pathway binds well to the core node. Finally, clinical prognostic analysis and expression differences of Hub genes were validated using the Cancer Genome Atlas database and R language. Our search yielded 152 common targets for GFW and CSCC. The interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and Toll-like signaling pathway were then selected for further molecular docking from the hub genes enrichment analysis results, which showed good binding. Among the Hub genes, JUN, VEGFA, IL1B, and EGF had a poor prognosis for CSCC. In conclusion, this study illustrates that GFW can have adjuvant therapeutic effects on CSCC through multiple targets and multiple pathways, providing a basis for further research.

Dissecting the role of ALK double mutations in drug resistance to lorlatinib with in-depth theoretical modeling and analysis.

Anaplastic lymphoma kinase (ALK) is implicated in the genesis of multiple malignant tumors. Lorlatinib stands out as the most advanced and effective inhibitor currently used in the clinic for the treatment of ALK-positive non-small cell lung cancer. However, resistance to lorlatinib has inevitably manifested over time, with double/triple mutations of G1202, L1196, L1198, C1156 and I1171 frequently observed in clinical practice, and tumors regrow within a short time after treatment with lorlatinib. Therefore, elucidating the mechanism of resistance to lorlatinib is paramount in paving the way for innovative therapeutic strategies and the development of next-generation drugs. In this study, we leveraged multiple computational methodologies to delve into the resistance mechanisms of three specific double mutations of ALKG1202R/L1196M, ALKG1202R/L1198F and ALKI1171N/L1198F to lorlatinib. We analyzed these mechanisms through qualitative (PCA, DCCM) and quantitative (MM/GBSA, US) kinetic analyses. The qualitative analysis shows that these mutations exert minimal perturbations on the conformational dynamics of the structural domains of ALK. The energetic and structural assessments show that the van der Waals interactions, formed by the conserved residue Leu1256 within the ATP-binding site and the residues Glu1197 and Met1199 in the hinge domain with lorlatinib, play integral roles in the occurrence of drug resistance. Furthermore, the US simulation results elucidate that the pathways through which lorlatinib dissociates vary across mutant systems, and the distinct environments during the dissociation process culminate in diverse resistance mechanisms. Collectively, these insights provide important clues for the design of novel inhibitors to combat resistance.

Counter-Doping Effect by Trivalent Cations in Tin-Based Perovskite Solar Cells.

Tin (Sn) -based perovskite solar cells (PSCs) normally show low open circuit voltage due to serious carrier recombination in the devices, which can be attributed to the oxidation and the resultant high p-type doping of the perovskite active layers. Considering the grand challenge to completely prohibit the oxidation of Sn-based perovskites, a feasible way to improve the device performance is to counter-dope the oxidized Sn-based perovskites by replacing Sn2+ with trivalent cations in the crystal lattice, which however is rarely reported. Here, the introduction of Sb3+, which can effectively counter-dope the oxidized perovskite layer and improve the carrier lifetime, is presented. Meanwhile, Sb3+ can passivate deep-level defects and improve carrier mobility of the perovskite layer, which are all favorable for the photovoltaic performance of the devices. Consequently, the target devices yield a relative enhancement of the power conversion efficiency (PCE) of 31.4% as well as excellent shelf-storage stability. This work provides a novel strategy to improve the performance of Sn-based PSCs, which can be developed as a universal way to compensate for the oxidation of Sn-based perovskites in optoelectronic devices.