Highly Stable Solid Contact Calcium Ion-Selective Electrodes: Rapid Ion-Electron Transduction Triggered by Lipophilic Anions Participating in Redox Reactions of CunS Nanoflowers.

Solid contact (SC) calcium ion-selective electrodes (Ca2+-ISEs) have been widely applied in the analysis of water quality and body fluids by virtue of the unique advantages of easy operation and rapid response. However, the potential drift during the long-term stability test hinders their further practical applications. Designing novel redox SC layers with large capacitance and high hydrophobicity is a promising approach to stabilize the potential stability, meanwhile, exploring the transduction mechanism is also of great guiding significance for the precise design of SC layer materials. Herein, flower-like copper sulfide (CunS-50) composed of nanosheets is meticulously designed as the redox SC layer by modification with the surfactant (CTAB). The CunS-50-based Ca2+-ISE (CunS-50/Ca2+-ISE) demonstrates a near-Nernstian slope of 28.23 mV/dec for Ca2+ in a wide activity linear range of 10-7 to 10-1 M, with a low detection limit of 3.16 × 10-8 M. CunS-50/Ca2+-ISE possesses an extremely low potential drift of only 1.23 ± 0.13 µV/h in the long-term potential stability test. Notably, X-ray absorption fine-structure (XAFS) spectra and electrochemical experiments are adopted to elucidate the transduction mechanism that the lipophilic anion (TFPB-) participates in the redox reaction of CunS-50 at the solid-solid interface of ion-selective membrane (ISM) and redox inorganic SC layer (CunS-50), thereby promoting the generation of free electrons to accelerate ion-electron transduction. This work provides an in-depth comprehension of the transduction mechanism of the potentiometric response and an effective strategy for designing redox materials of ion-electron transduction triggered by lipophilic anions.

Fully Integrated Multiplexed Wristwatch for Real-Time Monitoring of Electrolyte Ions in Sweat.

Considerable progress has already been made in sweat sensors based on electrochemical methods to realize real-time monitoring of biomarkers. However, realizing long-term monitoring of multiple targets at the atomic level remains extremely challenging, in terms of designing stable solid contact (SC) interfaces and fully integrating multiple modules for large-scale applications of sweat sensors. Herein, a fully integrated wristwatch was designed using mass-manufactured sensor arrays based on hierarchical multilayer-pore cross-linked N-doped porous carbon coated by reduced graphene oxide (NPCs@rGO-950) microspheres with high hydrophobicity as core SC, and highly selective monitoring simultaneously for K+, Na+, and Ca2+ ions in human sweat was achieved, exhibiting near-Nernst responses almost without forming an interfacial water layer. Combined with computed tomography, solid-solid interface potential diffusion simulation results reveal extremely low interface diffusion potential and high interface capacitance (598 µF), ensuring the excellent potential stability, reversibility, repeatability, and selectivity of sensor arrays. The developed highly integrated-multiplexed wristwatch with multiple modules, including SC, sensor array, microfluidic chip, signal transduction, signal processing, and data visualization, achieved reliable real-time monitoring for K+, Na+, and Ca2+ ion concentrations in sweat. Ingenious material design, scalable sensor fabrication, and electrical integration of multimodule wearables lay the foundation for developing reliable sweat-sensing systems for health monitoring.

A Curated Rotamer Library for Common Post-Translational Modifications of Proteins.

Sidechain rotamer libraries of the common amino acids of a protein are useful for folded protein structure determination and for generating ensembles of intrinsically disordered proteins (IDPs). However much of protein function is modulated beyond the translated sequence through thFiguree introduction of post-translational modifications (PTMs). In this work we have provided a curated set of side chain rotamers for the most common PTMs derived from the RCSB PDB database, including phosphorylated, methylated, and acetylated sidechains. Our rotamer libraries improve upon existing methods such as SIDEpro and Rosetta in predicting the experimental structures for PTMs in folded proteins. In addition, we showcase our PTM libraries in full use by generating ensembles with the Monte Carlo Side Chain Entropy (MCSCE) for folded proteins, and combining MCSCE with the Local Disordered Region Sampling algorithms within IDPConformerGenerator for proteins with intrinsically disordered regions.

New insights into functional divergence and adaptive evolution of uncultured bacteria in anammox community by complete genome-centric analysis.

Anaerobic ammonium-oxidation (anammox) bacteria play a crucial role in global nitrogen cycling and wastewater nitrogen removal, but they share symbiotic relationships with various other microorganisms. Functional divergence and adaptive evolution of uncultured bacteria in anammox community remain underexplored. Although shotgun metagenomics based on short reads has been widely used in anammox research, metagenome-assembled genomes (MAGs) are often discontinuous and highly contaminated, which limits in-depth analyses of anammox communities. Here, for the first time, we performed Pacific Biosciences high-fidelity (HiFi) long-read sequencing on the anammox granule sludge sample from a lab-scale bioreactor, and obtained 30 accurate and complete metagenome-assembled genomes (cMAGs). These cMAGs were obtained by selecting high-quality circular contigs from initial assemblies of long reads generated by HiFi sequencing, eliminating the need for Illumina short reads, binning, and reassembly. One new anammox species affiliated with Candidatus Jettenia and three species affiliated with novel families were found in this anammox community. cMAG-centric analysis revealed functional divergence in general and nitrogen metabolism among the anammox community members, and they might adopt a cross-feeding strategy in organic matter, cofactors, and vitamins. Furthermore, we identified 63 mobile genetic elements (MGEs) and 50 putative horizontal gene transfer (HGT) events within these cMAGs. The results suggest that HGT events and MGEs related to phage and integration or excision, particularly transposons containing tnpA in anammox bacteria, might play important roles in the adaptive evolution of this anammox community. The cMAGs generated in the present study could be used to establish of a comprehensive database for anammox bacteria and associated microorganisms. These findings highlight the advantages of HiFi sequencing for the studies of complex mixed cultures and advance the understanding of anammox communities.

Formulating N-Doped Carbon Hollow Nanospheres with Highly Accessible Through-Pores to Isolate Fe Single-Atoms for Efficient Oxygen Reduction.

It is challenging yet promising to design highly accessible N-doped carbon skeletons to fully expose the active sites inside single-atom catalysts. Herein, mesoporous N-doped carbon hollow spheres with regulatable through-pore size can be formulated by a simple sequential synthesis procedure, in which the condensed SiO2 is acted as removable dual-templates to produce both hollow interiors and through-pores, meanwhile, the co-condensed polydopamine shell is served as N-doped carbon precursor. After that, Fe─N─C hollow spheres (HSs) with highly accessible active sites can be obtained after rationally implanting Fe single-atoms. Microstructural analysis and X-ray absorption fine structure analysis reveal that high-density Fe─N4 active sites together with tiny Fe clusters are uniformly distributed on the mesoporous carbon skeleton with abundant through-pores. Benefitted from the highly accessible Fe─N4 active sites arising from the unique through-pore architecture, the Fe─N─C HSs demonstrate excellent oxygen reduction reaction (ORR) performance in alkaline media with a half-wave potential up to 0.90 V versus RHE and remarkable stability, both exceeding the commercial Pt/C. When employing Fe─N─C HSs as the air-cathode catalysts, the assembled Zn-air batteries deliver a high peak power density of 204 mW cm-2 and stable discharging voltage plateau over 140 h.

Ion-Electron Transduction Layer of the SnS2-MoS2 Heterojunction to Elevate Superior Interface Stability for All-Solid Sodium-Ion Selective Electrode.

The high selectivity and fast ion response of all-solid sodium ion selective electrodes were widely applied in human sweat analysis. However, the potential drift due to insufficient interfacial capacitance leads to the deterioration of its stability and ultimately affects the potential accuracy of ion analysis. Designing a novel ion-electron transduction layer between the electrode and the ion selective membrane is an effective method to stabilize the interfacial potential. Herein, the SnS2-MoS2 heterojunction material was constructed by doping Sn in MoS2 nanosheets and used as the ion electron transduction layers of an all-solid sodium ion selective electrode for the first time, achieving the stable and efficient detection of Na+ ions. The proposed electrode exhibited a Nernst slope of 57.86 mV/dec for the detection of Na+ ions with a detection limit of 10-5.7 M in the activity range of 10-6-10-1 M. Via the electronic interaction at the heterojunction interfaces between SnS2 and MoS2 materials, the micro-nanostructure of the SnS2-MoS2 heterojunction was changed and SnS2-MoS2 as the ion-electron transduction layer acquired excellent capacitance (699 µF) and hydrophobicity (132°), resulting in a long-term potential stability of 1.37 µV/h. It was further proved that the large capacitance and high hydrophobicity of the ion-electron transduction layer are primary reasons for the excellent stability of the all-solid sodium ion selective electrode toward Na+ ions.

Intramolecular Ni-catalyzed reductive coupling enables enantiodivergent synthesis of linoxepin.

A nickel-catalyzed reductive tandem cyclization of the elaborated ß-bromo acetal with a dibenzoxepin scaffold was invented to strategically construct the remaining two rings in linoxepin. The generated diasterodivergent intermediates could be easily converted to both enantiomers of this unique cyclolignan molecule via facile oxidations, thus realizing enantiodivergent total synthesis of linoxepin for the first time.

Local Disordered Region Sampling (LDRS) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments.

SUMMARY: The Local Disordered Region Sampling (LDRS, pronounced loaders) tool is a new module developed for IDPConformerGenerator, a previously validated approach to model intrinsically disordered proteins (IDPs). The IDPConformerGenerator LDRS module provides a method for generating all-atom conformations of intrinsically disordered protein regions at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB or mmCIF formatted structural template of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo-Side Chain Entropy, transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, the ability to be used as a library and via command-line, and the computational speed of the IDPConformerGenerator platform. AVAILABILITY AND IMPLEMENTATION: The LDRS module is part of the IDPConformerGenerator modeling suite, which can be downloaded from GitHub at https://github.com/julie-forman-kay-lab/IDPConformerGenerator. IDPConformerGenerator is written in Python3 and works on Linux, Microsoft Windows, and Mac OS versions that support DSSP. Users can utilize LDRS's Python API for scripting the same way they can use any part of IDPConformerGenerator's API, by importing functions from the "idpconfgen.ldrs_helper" library. Otherwise, LDRS can be used as a command line interface application within IDPConformerGenerator. Full documentation is available within the command-line interface as well as on IDPConformerGenerator's official documentation pages (https://idpconformergenerator.readthedocs.io/en/latest/).

Activation of caspase-9 on the apoptosome as studied by methyl-TROSY NMR.

Mitochondrial apoptotic signaling cascades lead to the formation of the apoptosome, a 1.1-MDa heptameric protein scaffold that recruits and activates the caspase-9 protease. Once activated, caspase-9 cleaves and activates downstream effector caspases, triggering the onset of cell death through caspase-mediated proteolysis of cellular proteins. Failure to activate caspase-9 enables the evasion of programmed cell death, which occurs in various forms of cancer. Despite the critical apoptotic function of caspase-9, the structural mechanism by which it is activated on the apoptosome has remained elusive. Here, we used a combination of methyl-transverse relaxation-optimized NMR spectroscopy, protein engineering, and biochemical assays to study the activation of caspase-9 bound to the apoptosome. In the absence of peptide substrate, we observed that both caspase-9 and its isolated protease domain (PD) only very weakly dimerize with dissociation constants in the millimolar range. Methyl-NMR spectra of isotope-labeled caspase-9, within the 1.3-MDa native apoptosome complex or an engineered 480-kDa apoptosome mimic, reveal that the caspase-9 PD remains monomeric after recruitment to the scaffold. Binding to the apoptosome, therefore, organizes caspase-9 PDs so that they can rapidly and extensively dimerize only when substrate is present, providing an important layer in the regulation of caspase-9 activation. Our work highlights the unique role of NMR spectroscopy to structurally characterize protein domains that are flexibly tethered to large scaffolds, even in cases where the molecular targets are in excess of 1 MDa, as in the present example.

Bile acids and their receptors: Potential therapeutic targets in inflammatory bowel disease.

Chronic and recurrent inflammatory disorders of the gastrointestinal tract caused by a complex interplay between genetics and intestinal dysbiosis are called inflammatory bowel disease. As a result of the interaction between the liver and the gut microbiota, bile acids are an atypical class of steroids produced in mammals and traditionally known for their function in food absorption. With the development of genomics and metabolomics, more and more data suggest that the pathophysiological mechanisms of inflammatory bowel disease are regulated by bile acids and their receptors. Bile acids operate as signalling molecules by activating a variety of bile acid receptors that impact intestinal flora, epithelial barrier function, and intestinal immunology. Inflammatory bowel disease can be treated in new ways by using these potential molecules. This paper mainly discusses the increasing function of bile acids and their receptors in inflammatory bowel disease and their prospective therapeutic applications. In addition, we explore bile acid metabolism and the interaction of bile acids and the gut microbiota.

Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments.

The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB structure of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo Side Chain Entropy (MC-SCE) (Bhowmick and Head-Gordon 2015), transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, ability to be used as a library and via command-line, and computational speed of the IDPConformerGenerator platform.

Danhong Injection Up-regulates miR-125b in Endothelial Exosomes and Attenuates Apoptosis in Post-Infarction Myocardium.

OBJECTIVE: To investigate the involvement of endothelial cells (ECs)-derived exosomes in the anti-apoptotic effect of Danhong Injection (DHI) and the mechanism of DHI-induced exosomal protection against postinfarction myocardial apoptosis. METHODS: A mouse permanent myocardial infarction (MI) model was established, followed by a 14-day daily treatment with DHI, DHI plus GW4869 (an exosomal inhibitor), or saline. Phosphate-buffered saline (PBS)-induced ECs-derived exosomes were isolated, analyzed by miRNA microarray and validated by droplet digital polymerase chain reaction (ddPCR). The exosomes induced by DHI (DHI-exo), PBS (PBS-exo), or DHI+GW4869 (GW-exo) were isolated and injected into the peri-infarct zone following MI. The protective effects of DHI and DHI-exo on MI hearts were measured by echocardiography, Masson's trichrome staining, and TUNEL apoptosis assay. The Western blotting and quantitative reverse transcription PCR (qRT-PCR) were used to evaluate the expression levels of miR-125b/p53-mediated pathway components, including miR-125b, p53, Bak, Bax, and caspase-3 activities. RESULTS: DHI significantly improved cardiac function and reduced infarct size in MI mice (P<0.01), which was abolished by the GW4869 intervention. DHI promoted the exosomal secretion in ECs (P<0.01). According to the results of exosomal miRNA microarray assay, 30 differentially expressed miRNAs in the DHI-exo were identified (28 up-regulated miRNAs and 2 down-regulated miRNAs). Among them, DHI significantly elevated miR-125b level in DHI-exo and DHI-treated ECs, a recognized apoptotic inhibitor impeding p53 signaling (P<0.05). Remarkably, treatment with DHI and DHI-exo attenuated apoptosis, elevated miR-125b expression level, inhibited capsase-3 activity, and down-regulated the expression levels of proapoptotic effectors (p53, Bak, and Bax) in post-MI hearts, whereas these effects were blocked by GW4869 (P<0.05 or P<0.01). CONCLUSION: DHI and DHI-induced exosomes inhibited apoptosis, promoted the miR-125b expression level, and regulated the p53 apoptotic pathway in post-infarction myocardium.

Delineating Structural Propensities of the 4E-BP2 Protein via Integrative Modeling and Clustering.

The intrinsically disordered 4E-BP2 protein regulates mRNA cap-dependent translation through interaction with the predominantly folded eukaryotic initiation factor 4E (eIF4E). Phosphorylation of 4E-BP2 dramatically reduces the level of eIF4E binding, in part by stabilizing a binding-incompatible folded domain. Here, we used a Rosetta-based sampling algorithm optimized for IDRs to generate initial ensembles for two phospho forms of 4E-BP2, non- and 5-fold phosphorylated (NP and 5P, respectively), with the 5P folded domain flanked by N- and C-terminal IDRs (N-IDR and C-IDR, respectively). We then applied an integrative Bayesian approach to obtain NP and 5P conformational ensembles that agree with experimental data from nuclear magnetic resonance, small-angle X-ray scattering, and single-molecule Förster resonance energy transfer (smFRET). For the NP state, inter-residue distance scaling and 2D maps revealed the role of charge segregation and pi interactions in driving contacts between distal regions of the chain (∼70 residues apart). The 5P ensemble shows prominent contacts of the N-IDR region with the two phosphosites in the folded domain, pT37 and pT46, and, to a lesser extent, delocalized interactions with the C-IDR region. Agglomerative hierarchical clustering led to partitioning of each of the two ensembles into four clusters with different global dimensions and contact maps. This helped delineate an NP cluster that, based on our smFRET data, is compatible with the eIF4E-bound state. 5P clusters were differentiated by interactions of C-IDR with the folded domain and of the N-IDR with the two phosphosites in the folded domain. Our study provides both a better visualization of fundamental structural poses of 4E-BP2 and a set of falsifiable insights on intrachain interactions that bias folding and binding of this protein.

Association of Socioeconomic Disparities With Nasopharyngeal Carcinoma Survival in an Endemic Area, China.

OBJECTIVES: This retrospective cohort study investigated the association of socioeconomic status with survival outcomes among patients with nasopharyngeal carcinoma in an endemic area of China. METHODS: The primary endpoint was overall survival. Survival outcomes were estimated by the Kaplan-Meier method and compared by the log-rank test, and the multivariate Cox proportional hazards model was used to estimate hazard ratios, 95% CIs, and independent prognostic factors. RESULTS: A total of 11 069 adult patients with NPC were enrolled and included in the analysis. Kaplan-Meier survival analysis revealed that overall survival was significantly different among socioeconomic status. Compared with high socioeconomic status patients, low socioeconomic status patients (HR, 1.190; 95% CI, 1.063-1.333) and medium socioeconomic status patients (HR, 1.111; 95% CI, 1.006-1.226) were associated with increased hazard ratio (HR) of overall survival. CONCLUSION: This analysis highlights patients with nasopharyngeal carcinoma who had high socioeconomic status had better overall survival compared with those who had low and medium socioeconomic status.

Outcomes of different zero-profile spacers in the treatment of two-level cervical degenerative disk disease.

PURPOSE: The purpose of this study was to analyze the clinical and radiological outcomes of two different zero-profile spacers (ROI-C and anchor-C) in contiguous two-level ACDF for CDDD patients. METHODS: We retrospectively analyzed patients who underwent contiguous two-level ACDF due to CDDD between January 2015 and December 2020 in our hospital. Patients who received ROI-C and anchor-C were included as the study groups, and those who underwent plate-cage construct (PCC) were included as the control group. The primary outcome measures were radiographical parameters, and the secondary outcome measures were dysphagia, JOA scores and VAS scores for these patients. RESULTS: A total of 91 patients were enrolled in the study; there were 31, 21 and 39 patients in the ROI-C, anchor-C and PCC groups, respectively. The mean follow-up duration was 24.52 months (range, 18-48 months) in the ROI-C group, 24.38 months (range, 16-52 months) in the anchor-C group and 25.18 months (range, 15-54 months) in the PCC group. The loss of the intervertebral space height and cage subsidence rate in the ROI-C group were significantly higher than those in the anchor-C group and PCC group at the final follow-up (P < 0.05). The ROI-C group showed a lower incidence of adjacent segment degeneration than the anchor-C group and PCC group, but the difference was not significant. The fusion rates were not different among these three groups. The early dysphagia rate was significantly lower in the patients with zero-profile spacers than in the PCC group (P < 0.05), but the difference was not significant at the last follow-up. No relevant differences were found in the JOA scores and VAS scores. CONCLUSIONS: Zero-profile spacers showed promising clinical outcomes in CDDD patients having contiguous two-level ACDF. However, ROI-C resulted in a higher intervertebral space height loss and a higher cage subsidence rate than anchor-C during the follow-up.

A Flexible Sensor with Excellent Environmental Stability Using Well-Designed Encapsulation Structure.

The hydrogel-based sensors suffer from poor stability and low sensitivity, severely limiting their further development. It is still "a black box" to understand the effect of the encapsulation as well as the electrode on the performance of the hydrogel-based sensors. To address these problems, we prepared an adhesive hydrogel that could robustly adhere to Ecoflex (adhesive strength is 4.7 kPa) as an encapsulation layer and proposed a rational encapsulation model that fully encapsulated the hydrogel within Ecoflex. Owing to the excellent barrier and resilience of Ecoflex, the encapsulated hydrogel-based sensor can still work normally after 30 days, displaying excellent long-term stability. In addition, we performed theoretical and simulation analyses on the contact state between the hydrogel and the electrode. It was surprising to find that the contact state significantly affects the sensitivity of the hydrogel sensors (the maximum difference in sensitivity was 333.6%), indicating that the reasonable design of the encapsulation and electrode are indispensable parts for fabricating successful hydrogel sensors. Therefore, we paved the way for a novel insight to optimize the properties of the hydrogel sensors, which is greatly favorable to developing hydrogel-based sensors to be applied in various fields.

Learning to evolve structural ensembles of unfolded and disordered proteins using experimental solution data.

The structural characterization of proteins with a disorder requires a computational approach backed by experiments to model their diverse and dynamic structural ensembles. The selection of conformational ensembles consistent with solution experiments of disordered proteins highly depends on the initial pool of conformers, with currently available tools limited by conformational sampling. We have developed a Generative Recurrent Neural Network (GRNN) that uses supervised learning to bias the probability distributions of torsions to take advantage of experimental data types such as nuclear magnetic resonance J-couplings, nuclear Overhauser effects, and paramagnetic resonance enhancements. We show that updating the generative model parameters according to the reward feedback on the basis of the agreement between experimental data and probabilistic selection of torsions from learned distributions provides an alternative to existing approaches that simply reweight conformers of a static structural pool for disordered proteins. Instead, the biased GRNN, DynamICE, learns to physically change the conformations of the underlying pool of the disordered protein to those that better agree with experiments.

3-Methyladenine ameliorates surgery-induced anxiety-like behaviors in aged mice by inhibiting autophagy-induced excessive oxidative stress.

BACKGROUND: Postoperative anxiety is a common surgical complication in older patients. Research has recently linked excessive autophagy to several neurological disorders, including anxiety. This study aimed to determine whether 3-Methyladenine (3-MA) administration reduced anxiety-like behaviors in a mouse model following abdominal exploratory laparotomy. METHODS: An abdominal exploratory laparotomy model of postoperative anxiety was established using male C57BL/6 mice aged 20 months. 3-MA (6, 30, and 150 mg/ml) was administered via intracerebroventricular immediately following surgery. The mice were assessed 14 days after surgery using the marble burying, elevated plus maze tests, and local field potential recording in the amygdala. The levels of expression of phosphorylated-Akt, Beclin-1, LC3B, nuclear factor erythroid 2-related factor 2 (Nrf2)-occupied regions in NeuN-positive cells, superoxide dismutase (SOD) activity, malondialdehyde (MDA), and glutathione (GSH) were measured at 24 h after surgery. RESULTS: The injection of 3-MA reversed the increased number of marbles buried, decreased time spent in the open arm, and enhanced θ oscillation power after 14 days of abdominal exploratory laparotomy. In addition, administration of 3-MA reduced the ratio of phosphorylated- to total-Akt, decreased expression in Beclin-1 and LC3B, attenuated MDA levels, and increased the ratio of Nrf2-occupied areas in NeuN-positive cells, SOD activity, and GSH levels under abdominal exploratory laparotomy conditions. CONCLUSIONS: 3-MA improved anxiety-like behaviors in aged mice undergoing abdominal exploratory laparotomy by inhibiting excessive autophagy-induced oxidative stress. These results suggest that 3-MA could be an effective treatment for postoperative anxiety.

Clinical outcomes and prediction nomogram model for postoperative hemoglobin < 80 g/L in patients following primary lumbar interbody fusion surgery.

OBJECTIVE: To analyze the association between different postoperative hemoglobin (Hb) levels and postoperative outcomes in patients who have undergone primary lumbar interbody fusion, and to investigate the risk factors and establish a predictive nomogram mode for postoperative Hb < 80 g/L. METHODS: We retrospectively analyzed 726 cases who underwent primary lumbar interbody fusion surgery between January 2018 and December 2021in our hospital. All patients were divided into three groups according to the postoperative Hb levels (< 70 g/L, 70-79 g/L, ≥ 80 g/L). The postoperative outcomes among the three groups were compared, and the risk factors for postoperative Hb < 80 g/L were identified by univariate and multivariable logistic regression analysis. Based on these independent predictors, a nomogram model was developed. Predictive discriminative and accuracy ability of the predicting model was assessed using the concordance index (C-index) and calibration plot. Clinical application was validated using decision curve analysis. Internal validation was performed using the bootstrapping validation. RESULTS: Patients with postoperative Hb < 80 g/L had higher rates of postoperative blood transfusion, a greater length of stay, higher rates of wound complications, and higher hospitalization costs than those with postoperative Hb ≥ 80 g/L. Preoperative Hb, preoperative platelets, fusion segments, body mass index, operation time, and intraoperative blood loss independently were associated with postoperative Hb < 80 g/L. Intraoperative blood salvage was found to be a negative predictor for postoperative Hb < 80 g/L (OR, 0.21 [95% CI 0.09-0.50]). The area under the curve of the nomogram model was 0.950. After internal validations, the C-index of the model was 0.939. The DCA and calibration curve suggested that the nomogram model had a good consistency and clinical utility. CONCLUSIONS: Postoperative Hb < 80 g/L in patients following primary lumbar interbody fusion surgery increased blood transfusions requirement and was independently associated with poor outcomes. A novel nomogram model was established and could conveniently predict the risk of postoperative Hb < 80 g/L in patients after this type of surgery.

Learning Correlations between Internal Coordinates to Improve 3D Cartesian Coordinates for Proteins.

We consider a generic representation problem of internal coordinates (bond lengths, valence angles, and dihedral angles) and their transformation to 3-dimensional Cartesian coordinates of a biomolecule. We show that the internal-to-Cartesian process relies on correctly predicting chemically subtle correlations among the internal coordinates themselves, and learning these correlations increases the fidelity of the Cartesian representation. We developed a machine learning algorithm, Int2Cart, to predict bond lengths and bond angles from backbone torsion angles and residue types of a protein, which allows reconstruction of protein structures better than using fixed bond lengths and bond angles or a static library method that relies on backbone torsion angles and residue types in a local environment. The method is able to be used for structure validation, as we show that the agreement between Int2Cart-predicted bond geometries and those from an AlphaFold 2 model can be used to estimate model quality. Additionally, by using Int2Cart to reconstruct an IDP ensemble, we are able to decrease the clash rate during modeling. The Int2Cart algorithm has been implemented as a publicly accessible python package at https://github.com/THGLab/int2cart.