Biogeography and diversity patterns of functional genes associated with C, N, P, S cycling processes across China classical sea sediments.

Microbial activities influence the ecological functions of marine ecosystems and play an essential role in biogeochemical cycling. However, there are more studies on microbial diversity and community structure, and few reports have explored nutrient cycling processes by microbial functional gene abundance and diversity. Given these limitations, in order to investigate the variability of nutrient cycling among different sea areas and its influencing factors, the sediments of the Bohai Sea, Yellow Sea, East China Sea and South China Sea were used in this study. The number of average copies of each functional gene was obtained by the quantitative microbial element cycling (QMEC) smart chip. A total of 65 functional genes related to C, N, P and S cycling were identified, and the results showed that all functional genes decreased in the order of magnitude from the Bohai Sea to the East China Sea, Yellow Sea and South China Sea, and the abundance of functional genes was significantly higher at the sampling sites near the land side, which related to human activities. Additionally, NH4+, organic carbon, total carbon and geographical factor were the main driving factors of functional gene composition changes (p < 0.05), and all functional genes were significantly correlated with total carbon and geographical distance (p < 0.01). These findings further expand the understanding of marine ecosystems and provide robust support for global biogeochemical cycles.

Exploring the human gut microbiota targets in relation to the use of contemporary antidepressants.

BACKGROUND: Antidepressants, specifically selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine reuptake inhibitors (SNRIs), are commonly prescribed for depression treatment. Animal studies have shown that antidepressants can influence gut microbiota composition and specific bacterial taxa. We aimed to investigate the association between antidepressant use and human gut microbiota composition and functional pathway. METHODS: We collected information on antidepressant use, demographic, food patterns, and clinical characteristics through questionnaires and medical records. The gut microbiota profiles of 271 depressive patients were carried out through 16S rRNA gene sequencing. Patients were categorized based on different types of antidepressant use groups for gut microbiota comparisons. MaAsLin2 was performed to evaluate microbiota composition across groups. PICRUSt2 was used to predict microbiota functional pathways. RESULTS: Patients taking SSRIs or SNRIs had a lower microbiota diversity. We found seven taxa abundances (Turicibacter, Barnesiella, Lachnospiraceae_ND3007_group, Romboutia, Akkermansia, Dialister, Romboutia and Fusicatenibacter) differed in patients with various types of antidepressants compared with those without antidepressant treatments (p < 0.05). Turicibacter inversely correlated with depression severity in SSRIs or SNRI users (r = -0.43, p < 0.05). Top identified pathways were related to compound fermentation and biosynthesis in microbiota function. CONCLUSION: Antidepressant usage, especially SSRIs and SNRIs, associates with changes in gut microbiota composition and specific taxa. Given our study's preliminary cross-sectional nature, further research is warranted to comprehend the relationship between antidepressant use, treatment response, and gut microbiota, aiming to enhance therapeutic interventions in the future.

Heavy metal migration regimes in the production of syngas from solid waste by thermal plasma treatment.

In recent years, thermal plasma technology has been widely used in the harmless and resource-efficient treatment of solid waste (SW). This study investigates the migration behaviors of heavy metals during the thermal plasma treats SW to obtain the interphase structure change regimes of heavy metals. The transformation of SW under high-temperature environments was analyzed by Fluent simulation, and the composition of the crystalline phases and heavy metal content of the post-treatment slags were studied through a combination of XRD, SEM, and heavy metal leaching experiments. The results show that the thermal plasma provides a melting zone temperature of more than 4000 K, and the treated slag is mostly an amorphous solid composed of glassy Si-O mesh, which effectively encapsulates heavy metals and reduces their leaching rate. Additional analysis of the migration and transformation of heavy metals during thermal plasma treatment revealed that solid-phase heavy metals primarily took the form of sulphides and sulphates, while liquid- and gas-phase heavy metals were mostly oxides and chlorides. Simultaneously, Economic analysis results showed that the thermal plasma treats SW economically with an Energetic efficiency of up to 76.7%. The results of this study providing new insights into thermal plasma treatment SW research.

RaT: Raman Transformer for highly accurate melanoma detection with critical features visualization.

Melanoma is an important cause of death from skin cancer. Early and accurate diagnosis can effectively reduce mortality. But the current diagnosis relies on the experience of pathologists, increasing the rate of misdiagnosis. In this paper, Raman Transformer (RaT) model is proposed by combining Raman spectroscopy and a Transformer encoder to distinguish the Raman spectra of melanoma and normal tissue. To make the spectral data more suitable for the Transformer encoder, we split the Raman spectrum into segments and map them into block vectors, which are then input into the Transformer encoder and classified using the multi-head self-attention mechanism and the Multilayer Perceptron (MLP). The RaT model achieves 99.69% accuracy, 99.61% sensitivity, and 99.82% specificity, which is higher than the classical principal component analysis with the neural network (PCA + NNET) method. In addition, we visualize and explain the fingerprint peaks found by the RaT model and their corresponding biological information. Our proposed RaT model provides a novel and reliable method for processing Raman spectral data, which is expected to help distinguish melanoma from normal cells, diagnose other diseases, and save human lives.

In-situ grown carbon as charge transfer medium for enhanced photoinduced electrons extraction from polymer carbon nitride toward TiO2.

Interfacial charge transfer resistance is one of the main limiting factors for realizing high photocatalytic efficiency of heterostructures system. Herein, an activated carbon layer is successfully introduced between the interface of polymer carbon nitride (CN) and TiO2 heterostructure (CNP-x) as charge transfer medium by in situ pyrolysis carbonization method. Because of the lower spatial resistance of the crystalline/amorphous interface and the fast carrier transportation character of activated carbon, the efficiency of TiO2 in extracting photoinduced electrons from CN was significantly improved. That is, the separation/transport of photocarriers in CNP-x heterostructure is accelerated, and the recombination time of photogenerated electrons and holes is prolonged. The CNP-1 exhibits a H2 evolution rate of 1298.5 µmol h-1 with apparent quantum yield (AQY) of 34.5 %, 20.3 % and 12.6 % at 365 nm, 380 nm and 400 nm, respectively. This work offers a novel and unique strategy to promote interface charge separation and transport of CN-based heterostructures by accurately introduction charge transfer medium.

Monolithic 3D structural-substrate SERS sensing platform for ultrasensitive and highly-specific analysis of trace bisphenol A.

Constructing advanced substrates with excellent features is promising for sensitive surface-enhanced Raman spectroscopy (SERS) detection. Here a novel capillary monolithic 3D structural-substrate SERS platform with Au@cDNA@Ag@Cyanine 3-aptamer nanoparticles (Au@cDNA@Ag@Cy3-Apt NPs) was fabricated for rapid, highly specific profiling of ultra-trace Bisphenol A (BPA). The proposed SERS platform combined both in-capillary SERS and aptamer-affinity recognition strategies, in which the superior SERS properties of Au-Ag NPs, aptamer selectivity, and the advantages of capillary monolith were integrated. A 3D hierarchically porous network was constructed in the monolithic column, which was endowed with rich hotspots for SERS, rapid sample permeation, and better analysis efficiency than most plane-shaped SERS modes. By varying the amount of Ag+ precursor, the Ag-shell thickness on SERS was finely tuned to guarantee Cy3 label in proximity to the plasmonic surface. Based on the biorecognition of aptamer, the selective identification of BPA occurred and exhibited a significant change in SERS intensity without obvious interference. As a result, the monolithic SERS platform featured facile operation, excellent specificity, and rapid analysis (10 min, much less than the solution-based or planar substrate SERS modes). Ultra-high sensitivity and robust reproducibility for BPA analysis was achieved with a low limit of detection (LOD) at 9.12 × 10-4 ng/L. The feasibility of this SERS platform for monitoring BPA in water and milk samples was also validated. This work lights a new access to capillary monolithic SERS-sensing platform for ultrasensitive and specific analysis of BPA.

Geographical origin identification of ginseng using near-infrared spectroscopy coupled with subspace-based ensemble classifiers.

Ginseng is a well-known traditional herbal medicine and the ginseng available on the market may not actually be produced in a certain place as claimed. Traditional methods of identifying the geographical origin of Ginseng are subjective, time-consuming or destructive. A more efficient approach is desirable. The feasibility of combining near-infrared (NIR) spectroscopy with ensemble learning for discriminating ginseng producing area was explored. A total of 270 samples were collected and evenly partitioned into the training and test sets. Random subspace ensemble (RSE) that uses linear discriminant classifier (LDA) as weak learner (abbreviated RSE-LDA) was used to construct predictive models. Two parameters including the size of subspace and the number of learners in ensemble were optimized. Classic partial least algorithm (PLS) was applied to build the reference model. The sensitivity, specificity, and total accuracy of final RSE-LDA and PLS models were 97.8 %, 100 %, 99.3 %, and 93.3 %, 96.7 %, 95.6 %, respectively. In order to study the impact of training set composition on the results, the samples were randomly divided 200 times and the algorithm was run repeatedly to statistically analyze the sensitivity and specificity on the test set. Similar results were obtained. The effect of training set size was also investigated. It indicates that the combination of NIR spectroscopy with the RSE algorithm is a potential tool of discriminating the origin of Ginseng.

GSDME has prognostic and immunotherapeutic significance in residual hepatocellular carcinoma after insufficient radiofrequency ablation.

BACKGROUND: Heat stress can induce programmed cell death (PCD). Pyroptosis is a gasdermin-mediated PCD. This study hypothesized that insufficient radiofrequency ablation (IRFA) induced pyroptosis in hepatocellular carcinoma (HCC) and investigated its underlying mechanism and clinical significance. METHODS: Thermostatic water bath was used to stimulate IRFA in vitro. Cell viability was assessed by MTT assay. IL-1ß and HMGB1 were measured by ELISA assay. LDH level was measured by LDH cytotoxicity detection kit. Permeability of cell membrane was assessed by Hoechst33342/PI fluorescence staining. RNA expression was evaluated by qRT-PCR, and protein was assessed by Western Blotting or immunofluorescence or immunohistochemistry. Gene expression with clinicopathological characteristics from HCC patients treated by RFA were analyzed for associations between GSDME expression and prognosis. RESULTS: Our study revealed that IRFA induced pyroptosis in HCCLM3 and HepG2 cells. GSDME, rather than GSDMD, was cleaved in heat stress-induced pyroptosis in HCCLM3 and HepG2 cells due to caspase-3 activation. However, GSDME overexpression promoted HCC growth in vivo and predicted poor PFS and OS in HCC patients treated by RFA. Heat stress modulated gene expression related to PD-L1 signaling and caspase inhibitors inhibited heat-induced PD-L1 expression in residual HCC after IRFA. Gsdme overexpression caused resistance to PD-L1 inhibitor in residual HCC after IRFA by increasing infiltrating of CD3+PD-1+ or CD3+CTLA-4+ exhausted T cells. CONCLUSIONS: This study indicated that GSDME could serve as a potential prognostic biomarker and help to prescribe personalized sequential immunotherapy for HCC patients receiving RFA.

Characterization and the mechanism underlying the cryoprotective activity of a peptide from large yellow croaker (Pseudosciaena crocea).

Ice crystal-induced protein denaturation is the main cause of the deterioration of fish during frozen storage and transportation. In this study, the ultra-performance liquid chromatography - quadrupole - time of flight (UPLC-Q-TOF) technique was used to identify and screen tryptic peptides Ile-Glu-Glu-Leu-Glu-Glu-Leu-Glu-Ala-Glu-Arg (IEELEEELEAER) from large yellow croaker (Pseudosciaena crocea). The results were used study their cryoprotective effects on turbot fish meat during freeze-thaw cycles at different concentrations, and to investigate their anti-freezing mechanism. The results showed that the I-2.0 group effectively inhibiting the degeneration and structure changes of myofibrillar proteins after three freeze-thaw cycles, and the Ca2+-ATPase activity (1.65 µmolPi/mg/h), increased by 55.86% compared with that of the control group. Additionally, peptide IEELEEELEAER could provide antifreeze protection by binding to the surface of ice crystals and inhibiting their transformation. This peptide acts as a natural cryoprotectant and might be used for the cryogenic storage and transportation of fish products.

Development of a prediction model for progression of coronary artery lesions in Kawasaki disease.

BACKGROUNDS: This study aimed to identify risk factors for the progression of coronary artery lesions (CALs) in children with Kawasaki disease (KD) and to develop a nomogram prediction model. METHODS: This is a retrospective case-control study in which the participants were categorized into three groups based on the changes of the maximum Z score (Zmax) of coronary arteries at the 1-month follow-up compared with the baseline Zmax: CALs-progressed, CALs-improved, and CALs-unchanged. RESULTS: Of total 387 patients, 65 (27%), 319 (73%), and 3 (0.7%) patients were categorized into CALs-progressed group, CALs-improved group, and CALs-unchanged group, respectively. Six independent factors associated with CALs progression were identified, including initial IVIG resistance, baseline Zmax, the number of coronary arteries involved, C-reactive protein, albumin, and soluble interleukin-2 receptor (odds ratio: 7.19, 1.51, 2.32, 1.52, 0.86, and 1.46, respectively; all P-values < 0.01). The nomogram prediction model including these six independent risk factors yielded an area under the curve (AUC) of 0.80 (95% confidence interval, 0.74 to 0.86). The accuracy of this model reached 81.7% after the Monte-Carlo Bootstrapping 1000 repetitions. CONCLUSIONS: The nomogram prediction model can identify children at high risk for the progression of CALs at early stages. IMPACT: Six independent factors associated with CALs progression were identified, including initial IVIG resistance, baseline Zmax, the number of coronary arteries involved, CRP, ALB, and sIL-2R. The prediction model we constructed can identify children at high risk for the progression of CALs at early stages and help clinicians make individualized treatment plans. Prospective, multi-centered studies with larger sample sizes are warranted to validate the power of this prediction model in children with KD.

Characterizing typhoon-related posttraumatic stress disorder based on multimodal fusion of structural, diffusion, and functional magnetic resonance imaging.

Diagnosing posttraumatic stress disorder (PTSD) using only single-modality images is controversial. We aimed to use multimodal magnetic resonance imaging (MRI) combining structural, diffusion, and functional MRI to possibly provide a more comprehensive viewpoint on the decisive characteristics of PTSD patients. Typhoon-exposed individuals with (n = 26) and without PTSD (n = 32) and healthy volunteers (n = 30) were enrolled. Five MRI features from three modalities, including two resting-state functional MRI (rs-fMRI) features (amplitude of low-frequency fluctuation, ALFF; and regional homogeneity, ReHo), one structural MRI feature (gray matter density, GM), and two diffusion tensor imaging (DTI) features (fractional anisotropy, FA; and mean diffusivity, MD) were investigated simultaneously with a multimodal canonical correlation analysis + joint independent component analysis model to identify abnormalities in the PTSD brain. We identified statistical differences between PTSD patients and healthy controls in terms of 1 rs-fMRI (ALFF, ReHo) alterations in the superior frontal gyrus, precuneus, inferior parietal lobule (IPL), anterior cingulate cortex (ACC), and posterior cingulate cortex (PCC), 2 DTI (FA, MD) changes in the pons, genu, and splenium of the corpus callosum, and 3 Structural MRI abnormalities in the precuneus, IPL, ACC, and PCC. A novel ReHo component was found to distinguish PTSD and trauma-exposed controls, including the precuneus, IPL, middle frontal gyrus, middle occipital gyrus, and cerebellum. This study reveals that PTSD individuals exhibit intertwined functional and structural anomalies within the default mode network. Some alterations within this network may serve as a potential marker to distinguish between PTSD patients and trauma-exposed controls.

Mechanochemical synthesis ionic covalent organic frameworks/cotton composites for pipette tip solid-phase extraction of domoic acid in seafood.

Pipette tip solid-phase extraction (PT-SPE) as a miniaturized solid-phase extraction technique have a wide range of applications in the field of sample pretreatment. In this study, ionic covalent organic frameworks@cotton (iCOF@cotton) were facilely synthesized by mechanochemical grinding method only in half an hour, and used as the adsorbents of PT-SPE. The synthesized iCOF@cotton not only had high specific surface area, suitable pore structure and cationic charge groups of iCOF that can extract polar targets quickly, but also reduced the problem of high back pressure of PT-SPE by the addition of cotton, thus accelerating extraction time. Combined with high performance liquid chromatographic tandem mass spectrometry (HPLC-MS/MS), an efficient and sensitive method was established for detection of domoic acid (DA, a toxin produced by algae). Under the optimal conditions, the proposed analysis method displayed excellent analytical performance, including broad range of linearity (10-1000 pg mL-1), low limit of detection (LOD, 5 pg mL-1), high correlation coefficient (0.9993), satisfactory precision (RSDs ≤6.4 %). In addition, the developed method was applied to the detection of DA in marine samples, and detected trace DA (18.6 pg mL-1) with satisfactory recovery (85.7%-107.2 %). The above results indicated that the prepared iCOF@cotton have great potential as the adsorbents for PT-SPE.

Infantile epileptic spasms syndrome: a cohort study of 88 children.

BACKGROUND: This study aimed to investigate and analyze the risk factors for non-etiology-specific infantile spasms (IS) and unrelieved clinical symptoms after treatment. METHODS: Eighty-eight children with IS who were treated at our hospital from March 2018 to December 2021 were included in the study. The children were divided into etiology-specific (n = 46) and nonetiology-specific (n = 42) groups, based on the diagnostic results, and remission (n = 45) and nonremission (n = 43) groups, based on clinical outcomes after treatment. The clinical data from patients in the etiology-specific and nonetiology-specific groups and the remission and nonremission groups were compared. Risk factors for non-etiology-specific IS were identified using logistic regression analysis. RESULTS: Gender, family history, birth status, and metabolic abnormalities were significantly different between the etiology-specific and non-etiology-specific groups. Gender and metabolic abnormalities were risk factors for nonetiology-specific IS. Family history, birth status, metabolic abnormalities, and brain magnetic resonance imaging were significantly different between the remission and nonremission groups, and different etiologies were risk factors for unrelieved symptoms after treatment. CONCLUSION: The occurrence of nonetiology-specific IS is associated with gender and metabolic abnormalities in children. After medication, unrelieved IS symptoms are associated with etiologies.

Associations between Alzheimer's disease biomarkers and postoperative delirium or cognitive dysfunction: A meta-analysis and trial sequential analysis of prospective clinical trials.

BACKGROUND: The relationship between Alzheimer's disease biomarkers and postoperative complications, such as postoperative delirium (POD) and postoperative cognitive dysfunction (POCD), remains a subject of ongoing debate. OBJECTIVE: This meta-analysis aimed to determine whether there is an association between perioperative Alzheimer's disease biomarkers and postoperative complications. DESIGN: We conducted a meta-analysis of observational clinical studies that explored the correlation between Alzheimer's disease biomarkers and POD or POCD in patients who have undergone surgery, following PRISMA guidelines. The protocol was previously published (INPLASY: INPLASY202350001). DATA SOURCES: A comprehensive search was conducted across PubMed, Embase, Web of Science, and Cochrane databases until March 2023. ELIGIBILITY CRITERIA: Surgical patients aged at least 18 years, studies focusing on POD or POCD, research involving Alzheimer's disease biomarkers, including Aß or tau in blood or cerebrospinal fluid (CSF), and availability of the full text. RESULTS: Our meta-analysis included 15 studies: six focusing on POD and nine on POCD. The findings revealed a negative correlation between preoperative CSF ß-amyloid 42 (Aß42) levels and the onset of POD [mean difference -86.1, 95% confidence interval (CI), -114.15 to -58.05, I2: 47%]; this association was strongly supported by trial sequential analysis (TSA). A similar negative correlation was discerned between preoperative CSF Aß42 levels and the incidence of POCD (-165.01, 95% CI, -261.48 to -68.53, I2: 95%). The TSA also provided robust evidence for this finding; however, the evidence remains insufficient to confirm a relationship between other Alzheimer's disease biomarkers [ß-amyloid 40 (Aß40), total tau (T-tau), phosphorylated tau (P-tau), and Aß42/T-tau ratio] and POD or POCD. CONCLUSION: The study results indicate a negative correlation between preoperative CSF Aß42 levels and the occurrence of both POD and POCD. Future investigations are warranted to identify the predictive cutoff value of preoperative CSF Aß42 for POD and POCD.

Predicting extubation in patients with traumatic cervical spinal cord injury using the diaphragm electrical activity during a single maximal maneuver.

BACKGROUND: The unsuccessful extubation in patients with traumatic cervical spinal cord injuries (CSCI) may result from impairment diaphragm function and monitoring of diaphragm electrical activity (EAdi) can be informative in guiding extubation. We aimed to evaluate whether the change of EAdi during a single maximal maneuver can predict extubation outcomes in CSCI patients. METHODS: This is a retrospective study of CSCI patients requiring mechanical ventilation in the ICU of a tertiary hospital. A single maximal maneuver was performed by asking each patient to inhale with maximum strength during the first spontaneous breathing trial (SBT). The baseline (during SBT before maximal maneuver), maximum (during the single maximal maneuver), and the increase of EAdi (ΔEAdi, equal to the difference between baseline and maximal) were measured. The primary outcome was extubation success, defined as no reintubation after the first extubation and no tracheostomy before any extubation during the ICU stay. RESULTS: Among 107 patients enrolled, 50 (46.7%) were extubated successfully at the first SBT. Baseline EAdi, maximum EAdi, and ΔEAdi were significantly higher, and the rapid shallow breathing index was lower in patients who were extubated successfully than in those who failed. By multivariable logistic analysis, ΔEAdi was independently associated with successful extubation (OR 2.03, 95% CI 1.52-3.17). ΔEAdi demonstrated high diagnostic accuracy in predicting extubation success with an AUROC 0.978 (95% CI 0.941-0.995), and the cut-off value was 7.0 µV. CONCLUSIONS: The increase of EAdi from baseline SBT during a single maximal maneuver is associated with successful extubation and can help guide extubation in CSCI patients.

Long-term management and treatment of acute intermittent porphyria with recurring attacks using pharmacological prophylaxis.

BACKGROUND: There is no definitive guidance on whether patients with acute intermittent porphyria (AIP) with recurrent attacks need pharmacological prophylactic treatment. METHODS: The management strategies for patients with frequent (defined as ≥4 annualized attack rate (AAR) and less frequent attacks (<4 AAR), including treatment for acute attacks and duration of prophylaxis (weekly heme arginate 3 mg/kg body weight and/or investigational drug, givosiran), were summarized. The AAR for the following periods were presented: the first 2 years after diagnosis, before/after prophylaxis, and the most recent 2 years. RESULTS: A total of 29 patients with AIP were included, 19 (34.5%) had <4 AAR and 10 (65.6%) had ≥4 AAR in the first 2 years after diagnosis. All patients experienced reduced attacks during the treatment course, 23 (79.3%) were attack-free during the most recent 2 years. Among the 9 patients who received prophylaxis (7 heme arginate; 1 givosiran, 1 heme arginate followed by givosiran), 5 (55.6%) were attack-free in the most recent 2-year period and prophylaxis was discontinued because there had been no attacks for >1 year. For patients without prophylaxis (n = 20), 18 (90.0%) were attack-free in the most recent 2-year period and 15 (75.0%) experienced attacks only in the first 2 years after diagnosis. CONCLUSIONS: Prophylaxis could be considered for patients with AIP with ≥4 biochemically confirmed attacks/year after routine treatment of 1-2 years, during which the severity and frequency of attacks should be closely monitored to determine the necessity of pharmacologic prophylaxis. More studies are needed to reach a consensus on the use of pharmacological prophylaxis and treatment of AIP.

Long-term outcome of children with acute promyelocytic leukemia: a randomized study of oral versus intravenous arsenic by SCCLG-APL group.

Realgar-Indigo naturalis formula (RIF), an oral traditional Chinese medicine mainly containing Realgar (As4S4), is highly effective in treating adult acute promyelocytic leukemia (APL). However, the treatment efficacy and safety of RIF have not been verified in pediatric patients. SCCLG-APL group conducted a multicenter randomized non-inferiority trial to determine whether intravenous arsenic trioxide (ATO) can be substituted by oral RIF in treating pediatric APL. Of 176 eligible patients enrolled, 91 and 85 were randomized to ATO and RIF groups, respectively. Patients were treated with the risk-adapted protocol. Induction, consolidation, and 96-week maintenance treatment contained all-trans-retinoic acid and low-intensity chemotherapy, and either ATO or RIF. The primary endpoint was 5-year event-free survival (EFS). The secondary endpoints were adverse events and hospital days. After a median 6-year follow-up, the 5-year EFS was 97.6% in both groups. However, the RIF group had significantly shorter hospital stays and lower incidence of infection and tended to have less cardiac toxicity. All 4 relapses occurred within 1.5 years after completion of maintenance therapy. No long-term arsenic retentions were observed in either group. Substituting oral RIF for ATO maintains treatment efficacy while reducing hospitalization and adverse events in treating pediatric APL patients, which may be a future treatment strategy for APL.

Disentangling the evolution of electrons and holes in photoexcited ZnO nanoparticles.

The evolution of charge carriers in photoexcited room temperature ZnO nanoparticles in solution is investigated using ultrafast ultraviolet photoluminescence spectroscopy, ultrafast Zn K-edge absorption spectroscopy, and ab initio molecular dynamics (MD) simulations. The photoluminescence is excited at 4.66 eV, well above the band edge, and shows that electron cooling in the conduction band and exciton formation occur in <500 fs, in excellent agreement with theoretical predictions. The x-ray absorption measurements, obtained upon excitation close to the band edge at 3.49 eV, are sensitive to the migration and trapping of holes. They reveal that the 2 ps transient largely reproduces the previously reported transient obtained at 100 ps time delay in synchrotron studies. In addition, the x-ray absorption signal is found to rise in ∼1.4 ps, which we attribute to the diffusion of holes through the lattice prior to their trapping at singly charged oxygen vacancies. Indeed, the MD simulations show that impulsive trapping of holes induces an ultrafast expansion of the cage of Zn atoms in <200 fs, followed by an oscillatory response at a frequency of ∼100 cm-1, which corresponds to a phonon mode of the system involving the Zn sub-lattice.

The diagnostic performance of V' and U' variables as an objective index of pink-color sign for diagnosing esophageal cancerous lesions.

BACKGROUND: The pink-color sign (PCS) has been widely used for diagnosing esophageal squamous cell carcinoma (ESCC) during Lugol's iodine chromoendoscopy. However, the identification of the PCS only relies on the subjective assessments made by the endoscopist, which could lead to bias and disagreement. Previous research has indicated that the V' variable can, as an objective index, define the PCS in the LU'V' color space. We aimed to validate the diagnostic performance of the PCS defined by the V' variable alone and attempt to improve the diagnostic performance by combining the V' and U' variables. METHODS: We re-examined 231 subjects with Lugol's unstained lesions (LULs) from a previously reported prospective trial. The diagnostic performance of the method using V' variable alone (V' alone method), the combination method using V' and U' variables (V' + U' method), and the endoscopists were calculated and compared. RESULTS: A total of 236 LULs were included, among which 46 were histologically confirmed to be cancerous lesions. The sensitivity, specificity, and accuracy of the V' alone method were 73.91% (95% CI 58.87-85.73%), 79.47% (95% CI 73.03-84.98%), and 78.39% (95% CI 72.59-83.47%) in the external validation cohort, respectively. It is inferior to endoscopists in terms of specificity and accuracy. The V' + U' method demonstrated a diagnostic performance comparable to the experienced endoscopists, with sensitivity, specificity, and accuracy of 76.74% (95% CI 61.37-88.25%), 88.64% (95% CI 83.00-92.92%), and 86.30% (95% CI 81.03-90.56%), respectively. CONCLUSION: The V' alone method exhibited lower specificity and accuracy than the experienced endoscopist and the V' + U' method. However, the modified V' + U' method demonstrated a diagnostic performance comparable to experienced endoscopists. Utilizing the objective index of the PCS could provide valuable support in clinical decision-making.

Development of genomic phenotype and immunophenotype of acute respiratory distress syndrome using autophagy and metabolism-related genes.

Background: Distinguishing ARDS phenotypes is of great importance for its precise treatment. In the study, we attempted to ascertain its phenotypes based on metabolic and autophagy-related genes and infiltrated immune cells. Methods: Transcription datasets of ARDS patients were obtained from Gene expression omnibus (GEO), autophagy and metabolic-related genes were from the Human Autophagy Database and the GeneCards Database, respectively. Autophagy and metabolism-related differentially expressed genes (AMRDEGs) were further identified by machine learning and processed for constructing the nomogram and the risk prediction model. Functional enrichment analyses of differentially expressed genes were performed between high- and low-risk groups. According to the protein-protein interaction network, these hub genes closely linked to increased risk of ARDS were identified with CytoHubba. ssGSEA and CIBERSORT was applied to analyze the infiltration pattern of immune cells in ARDS. Afterwards, immunologically characterized and molecular phenotypes were constructed according to infiltrated immune cells and hub genes. Results: A total of 26 AMRDEGs were obtained, and CTSB and EEF2 were identified as crucial AMRDEGs. The predictive capability of the risk score, calculated based on the expression levels of CTSB and EEF2, was robust for ARDS in both the discovery cohort (AUC = 1) and the validation cohort (AUC = 0.826). The mean risk score was determined to be 2.231332, and based on this score, patients were classified into high-risk and low-risk groups. 371 differential genes in high- and low-risk groups were analyzed. ITGAM, TYROBP, ITGB2, SPI1, PLEK, FGR, MPO, S100A12, HCK, and MYC were identified as hub genes. A total of 12 infiltrated immune cells were differentially expressed and have correlations with hub genes. According to hub genes and implanted immune cells, ARDS patients were divided into two different molecular phenotypes (Group 1: n = 38; Group 2: n = 19) and two immune phenotypes (Cluster1: n = 22; Cluster2: n = 35), respectively. Conclusion: This study picked up hub genes of ARDS related to autophagy and metabolism and clustered ARDS patients into different molecular phenotypes and immunophenotypes, providing insights into the precision medicine of treating patients with ARDS.