Highly Selective Novel Heme Oxygenase-1 Hits Found by DNA-Encoded Library Machine Learning beyond the DEL Chemical Space.

DNA-encoded library (DEL) technology, especially when combined with machine learning (ML), is a powerful method to discover novel inhibitors. DEL-ML can expand a larger chemical space and boost cost-effectiveness during hit finding. Heme oxygenase-1 (HO-1), a heme-degrading enzyme, is linked to diseases such as cancer and neurodegenerative disorders. The discovery of five series of new scaffold HO-1 hits is reported here, using a DEL-ML workflow, which emphasizes the model's uncertainty quantification and domain of applicability. This model exhibits a strong extrapolation ability, identifying new structures beyond the DEL chemical space. About 37% of predicted molecules showed a binding affinity of K D < 20 µM, with the strongest being 141 nM, amd 14 of those molecules displayed >100-fold selectivity for HO-1 over heme oxygenase-2 (HO-2). These molecules also showed structural novelty compared to existing HO-1 inhibitors. Docking simulations provided insights into possible selectivity rationale.

Analysis of metastasis­related risk factors and clinical relevance in adult soft­tissue sarcoma.

Metastasis occurs in nearly 50% of cases of adult soft-tissue sarcoma (ASTS), leading to a dismal prognosis, with a 2-year survival rate of ~30%. Consequently, a prognostic model that incorporates metastatic characteristics may be instrumental in predicting survival time and in crafting optimal personalized therapeutic strategies for patients with ASTS. In the present study, a prognostic prediction model for ASTS was developed by examining genes that are differentially expressed between non-metastatic and metastatic patients in the Gene Expression Omnibus dataset. The prognostic model, which includes five featured genes [actin γ2 (ACTG2), apolipoprotein D, coatomer protein complex subunit γ2 imprinted transcript 1, collagen type VI α6 chain and osteomodulin], was further validated in patients with ASTS from the Cancer Genome Atlas dataset. Based on these five-gene signatures, patients were categorized into high- and low-risk groups. Functional and pathway analyses revealed disparities in stemness, extracellular matrix and cell adhesion-related pathways between the two risk groups, particularly noting the activation of the PI3K-Akt pathway in high-risk cases. Analysis of immune infiltration also revealed variations in immune microenvironment changes between the two risk groups. Immunohistochemical staining substantiated the prognostic significance of these gene signatures in a specific sarcoma subtype. Additionally, wound-healing and Transwell assays demonstrated that inhibition of ACTG2 by shRNAs curbed cell migration and invasion in a sarcoma HOS cell line, underscoring its role in sarcoma metastasis. In conclusion, the present study successfully developed and validated a metastasis-based prognosis prediction model. This model not only reliably forecasts the survival of patients with ASTS, but also may pave the way for further investigation into the processes underlying sarcoma metastasis, ultimately aiding in the design of tailored therapeutic regimens.

Interference of FZD2 suppresses proliferation, vasculogenic mimicry and stemness in glioma cells via blocking the Notch/NF­κB signaling pathway.

Frizzled family protein 2 (FZD2) is widely associated with tumor development and metastasis. The present study aimed to gain an insight into the role and regulatory mechanism of FZD2 in glioma. The expression level of FZD2 in normal astrocyte and glioma cells was determined by reverse transcription-quantitative PCR and western blotting, and cell transfection was conducted for FZD2 expression knockdown. Malignant behaviors including cell proliferation, migration and invasion, vasculogenic mimicry (VM) and cell stemness were determined using Cell Counting Kit-8, 5-Ethynyl-2'-deoxyuridine (EdU) staining, colony formation, wound healing, Transwell, 3D culturing and sphere formation assays. The expression levels of proteins related to stemness, epithelial-mesenchymal transition (EMT) and Notch/NF-κB signaling were measured by western blotting. Then, the Notch agonist, Jagged-1 (JAG), was adopted for rescue experiments. The results demonstrated that FZD2 was highly expressed in glioma cells. Interference of FZD2 expression suppressed the proliferation of glioma cells, as evidenced by the reduced cell viability and the number of EdU+ cells and colonies. Meanwhile, the reduced sphere formation ability and decreased protein expression of Nanog, Sox2 and Oct4 following FZD2 knockdown confirmed that FZD2 repressed cell stemness in glioma. Additionally, FZD2 knockdown suppressed the migration, invasion, EMT and VM formation capabilities of glioma cells, and also blocked the Notch/NF-κB signaling pathway. Furthermore, activation of Notch by JAG treatment partially reversed the aforementioned FZD2 knockdown-mediated changes in glioma cell malignant behaviors. In conclusion, FZD2 may contribute to glioma progression through activating the Notch/NF-κB signaling pathway, providing a plausible therapeutic target for the treatment of glioma.

Ultrasonic Imaging of Deeper Bone Defect Using Virtual Source Synthetic Aperture with Phased Shift Migration: A Phantom Study.

Ultrasound imaging for bone is a difficult task in the field of medical ultrasound. Compared with other phase array techniques, the synthetic aperture (SA) has a better lateral resolution but a limited imaging depth due to the limited ultrasonic energy emitted by the single emitter in each transmission. In contrast, the virtual source (VS) synthetic aperture allows a simultaneous multi-element emission and could provide a higher ultrasonic incident energy in each transmission. Therefore, the VS might achieve a high imaging quality at a deeper depth for bone imaging than the traditional SA. In this study, we proposed the virtual source phase shift migration (VS-PSM) method to achieve ultrasonic imaging of the deeper bone defect featured in the multilayer structure. The proposed VS-PSM method was validated using standard soft tissue phantom and printed bone phantom with artificial defects. The image quality was evaluated in terms of contrast-to-noise ratios (CNR) and amplitudes of scatters and defects at different imaging depths. The results showed that the VS-PSM method could achieve a high imaging quality of the soft tissues with a significant improvement in the scattering amplitude and without a significant sacrifice of the lateral and axial resolution. The PSM was superior to the DAS in suppressing the background noise in the images. Compared with the traditional SA-PSM, the VS-PSM method could image deeper bone defects at different ultrasonic frequencies, with an average improvement of 50% in CNR. In conclusion, this study demonstrated that the proposed VS-PSM method could image deeper bone defects and might help the diagnosis of bone disease using ultrasonic imaging.

Genetically supported causality between gut microbiota and frailty: a two-sample Mendelian randomization study.

Background: A mounting body of evidence suggests a strong connection between gut microbiota and the risk of frailty. However, the question of causality remains unanswered. In this study, we employed a Mendelian randomization (MR) approach to assess potential causal relationships between gut microbiota and the risk of frailty. Materials and methods: Summary statistics for the gut microbiome were obtained from a genome wide association study (GWAS) meta-analysis of the MiBioGen consortium (N = 18,340). Summary statistics for frailty were obtained from a GWAS meta-analysis, including the UK Biobank and TwinGene (N = 175,226). Our primary analysis utilized the inverse variance weighted (IVW) method. To enhance the robustness of our results, we also applied weighted median methods, MR Egger regression, and MR pleiotropy residual sum and outlier test. Finally, we conducted reverse MR analysis to investigate the potential for reverse causality. Results: IVW method identified 7 bacterial taxa nominally associated with the risk of FI. Class Bacteroidia (p = 0.033) and genus Eubacterium ruminantium group (p = 0.028) were protective against FI. In addition, class Betaproteobacteria (p = 0.042), genus Allisonella (p = 0.012), genus Bifidobacterium (p = 0.013), genus Clostridium innocuum group (p = 0.036) and genus Eubacterium coprostanoligenes group (p = 0.003) were associated with a higher risk of FI. No pleiotropy or heterogeneity were found. Conclusion: The MR analysis indicates a causal relationship between specific gut microbiota and FI, offering new insights into the mechanisms underlying FI mediated by gut microbiota.

Evaluating the use of three-dimensional reconstruction visualization technology for precise laparoscopic resection in gastroesophageal junction cancer.

BACKGROUND: Laparoscopic gastrectomy for esophagogastric junction (EGJ) carcinoma enables the removal of the carcinoma at the junction between the stomach and esophagus while preserving the gastric function, thereby providing patients with better treatment outcomes and quality of life. Nonetheless, this surgical technique also presents some challenges and limitations. Therefore, three-dimensional reconstruction visualization technology (3D RVT) has been introduced into the procedure, providing doctors with more comprehensive and intuitive anatomical information that helps with surgical planning, navigation, and outcome evaluation. AIM: To discuss the application and advantages of 3D RVT in precise laparoscopic resection of EGJ carcinomas. METHODS: Data were obtained from the electronic or paper-based medical records at The First Affiliated Hospital of Hebei North University from January 2020 to June 2022. A total of 120 patients diagnosed with EGJ carcinoma were included in the study. Of these, 68 underwent laparoscopic resection after computed tomography (CT)-enhanced scanning and were categorized into the 2D group, whereas 52 underwent laparoscopic resection after CT-enhanced scanning and 3D RVT and were categorized into the 3D group. This study had two outcome measures: the deviation between tumor-related factors (such as maximum tumor diameter and infiltration length) in 3D RVT and clinical reality, and surgical outcome indicators (such as operative time, intraoperative blood loss, number of lymph node dissections, R0 resection rate, postoperative hospital stay, postoperative gas discharge time, drainage tube removal time, and related complications) between the 2D and 3D groups. RESULTS: Among patients included in the 3D group, 27 had a maximum tumor diameter of less than 3 cm, whereas 25 had a diameter of 3 cm or more. In actual surgical observations, 24 had a diameter of less than 3 cm, whereas 28 had a diameter of 3 cm or more. The findings were consistent between the two methods (χ2 = 0.346, P = 0.556), with a kappa consistency coefficient of 0.808. With respect to infiltration length, in the 3D group, 23 patients had a length of less than 5 cm, whereas 29 had a length of 5 cm or more. In actual surgical observations, 20 cases had a length of less than 5 cm, whereas 32 had a length of 5 cm or more. The findings were consistent between the two methods (χ2 = 0.357, P = 0.550), with a kappa consistency coefficient of 0.486. Pearson correlation analysis showed that the maximum tumor diameter and infiltration length measured using 3D RVT were positively correlated with clinical observations during surgery (r = 0.814 and 0.490, both P < 0.05). The 3D group had a shorter operative time (157.02 ± 8.38 vs 183.16 ± 23.87), less intraoperative blood loss (83.65 ± 14.22 vs 110.94 ± 22.05), and higher number of lymph node dissections (28.98 ± 2.82 vs 23.56 ± 2.77) and R0 resection rate (80.77% vs 61.64%) than the 2D group. Furthermore, the 3D group had shorter hospital stay [8 (8, 9) vs 13 (14, 16)], time to gas passage [3 (3, 4) vs 4 (5, 5)], and drainage tube removal time [4 (4, 5) vs 6 (6, 7)] than the 2D group. The complication rate was lower in the 3D group (11.54%) than in the 2D group (26.47%) (χ2 = 4.106, P < 0.05). CONCLUSION: Using 3D RVT, doctors can gain a more comprehensive and intuitive understanding of the anatomy and related lesions of EGJ carcinomas, thus enabling more accurate surgical planning.

Developing a geographical-meteorological indicator system and evaluating prediction models for alveolar echinococcosis in China.

BACKGROUND: Geographical and meteorological factors have been reported to influence the prevalence of echinococcosis, but there's a lack of indicator system and model. OBJECTIVE: To provide further insight into the impact of geographical and meteorological factors on AE prevalence and establish a theoretical basis for prevention and control. METHODS: Principal component and regression analysis were used to screen and establish a three-level indicator system. Relative weights were examined to determine the impact of each indicator, and five mathematical models were compared to identify the best predictive model for AE epidemic levels. RESULTS: By analyzing the data downloaded from the China Meteorological Data Service Center and Geospatial Data Cloud, we established the KCBIS, including 50 basic indicators which could be directly obtained online, 15 characteristic indicators which were linear combination of the basic indicators and showed a linear relationship with AE epidemic, and 8 key indicators which were characteristic indicators with a clearer relationships and fewer mixed effects. The relative weight analysis revealed that monthly precipitation, monthly cold days, the difference between negative and positive temperature anomalies, basic air temperature conditions, altitude, the difference between positive and negative atmospheric pressure anomalies, monthy extremely hot days, and monthly fresh breeze days were correlated with the natural logarithm of AE prevalence, with sequential decreases in their relative weights. The multinomial logistic regression model was the best predictor at epidemic levels 1, 3, 5, and 6, whereas the CART model was the best predictor at epidemic levels 2, 4, and 5.

Super-resolution reconstruction of ultrasound image using a modified diffusion model.

Objective. This study aims to perform super-resolution (SR) reconstruction of ultrasound images using a modified diffusion model, designated as the diffusion model for ultrasound image super-resolution (DMUISR). SR involves converting low-resolution images to high-resolution ones, and the proposed model is designed to enhance the suitability of diffusion models for this task in the context of ultrasound imaging.Approach. DMUISR incorporates a multi-layer self-attention (MLSA) mechanism and a wavelet-transform based low-resolution image (WTLR) encoder to enhance its suitability for ultrasound image SR tasks. The model takes interpolated and magnified images as input and outputs high-quality, detailed SR images. The study utilized 1,334 ultrasound images from the public fetal head-circumference dataset (HC18) for evaluation.Main results. Experiments were conducted at 2× , 4× , and 8×  magnification factors. DMUISR outperformed mainstream ultrasound SR methods (Bicubic, VDSR, DECUSR, DRCN, REDNet, SRGAN) across all scales, providing high-quality images with clear structures and rich detailed textures in both hard and soft tissue regions. DMUISR successfully accomplished multiscale SR reconstruction while suppressing over-smoothing and mode collapse problems. Quantitative results showed that DMUISR achieved the best performance in terms of learned perceptual image patch similarity, with a significant decrease of over 50% at all three magnification factors (2× , 4× , and 8× ), as well as improvements in peak signal-to-noise ratio and structural similarity index measure. Ablation experiments validated the effectiveness of the MLSA mechanism and WTLR encoder in improving DMUISR's SR performance. Furthermore, by reducing the number of diffusion steps, the computational time of DMUISR was shortened to nearly one-tenth of its original while maintaining image quality without significant degradation.Significance. This study demonstrates that the modified diffusion model, DMUISR, provides superior performance for SR reconstruction of ultrasound images and has potential in improving imaging quality in the medical ultrasound field.

Backscatter measurement of cancellous bone using the ultrasound transit time spectroscopy.

Recently, ultrasound transit time spectroscopy (UTTS) was proposed as a promising method for bone quantitative ultrasound measurement. Studies have showed that UTTS could estimate the bone volume fraction and other trabecular bone structure in ultrasonic through-transmission measurements. The goal of this study was to explore the feasibility of UTTS to be adapted in ultrasonic backscatter measurement and further evaluate the performance of backscattered ultrasound transit time spectrum (BS-UTTS) in the measurement of cancellous bone density and structure. First, taking ultrasonic attenuation into account, the concept of BS-UTTS was verified on ultrasonic backscatter signals simulated from a set of scatterers with different positions and intensities. Then, in vitro backscatter measurements were performed on 26 bovine cancellous bone specimens. After a logarithmic compression of the BS-UTTS, a linear fitting of the log-compressed BS-UTTS versus ultrasonic propagated distance was performed and the slope and intercept of the fitted line for BS-UTTS were determined. The associations between BS-UTTS parameters and cancellous bone features were analyzed using simple linear regression. The results showed that the BS-UTTS could make an accurate deconvolution of the backscatter signal and predict the position and intensity of the simulated scatterers eliminating phase interference, even the simulated backscatter signal was with a relatively low signal-to-noise ratio. With varied positions and intensities of the scatterers, the slope of the fitted line for the log-compressed BS-UTTS versus ultrasonic propagated distance (i.e., slope of BS-UTTS for short) yield a high agreement (r2 = 99.84%-99.96%) with ultrasonic attenuation in simulated backscatter signal. Compared with the high-density cancellous bone, the low-density specimen showed more abundant backscatter impulse response in the BS-UTTS. The slope of BS-UTTS yield a significant correlation with bone mineral density (r = 0.87; p < 0.001), BV/TV (r = 0.87; p < 0.001), and cancellous bone microstructures (r up to 0.87; p < 0.05). The intercept of BS-UTTS was also significantly correlated with bone densities (r = -0.87; p < 0.001) and trabecular structures (|r|=0.43-0.80; p < 0.05). However, the slope of the BS-UTTS underestimated attenuation when measurements were performed experimentally. In addition, a significant non-linear relationship was observed between the measured attenuation and the attenuation estimated by the slope of the BS-UTTS. This study demonstrated that the UTTS method could be adapted to ultrasonic backscatter measurement of cancellous bone. The derived slope and intercept of BS-UTTS could be used in the measurement of bone density and microstructure. The backscattered ultrasound transit time spectroscopy might have potential in the diagnosis of osteoporosis in the clinic.

Assessment and analysis of accents in air traffic control speech: a fusion of deep learning and information theory.

Introduction: Enhancing the generalization and reliability of speech recognition models in the field of air traffic control (ATC) is a challenging task. This is due to the limited storage, difficulty in acquisition, and high labeling costs of ATC speech data, which may result in data sample bias and class imbalance, leading to uncertainty and inaccuracy in speech recognition results. This study investigates a method for assessing the quality of ATC speech based on accents. Different combinations of data quality categories are selected according to the requirements of different model application scenarios to address the aforementioned issues effectively. Methods: The impact of accents on the performance of speech recognition models is analyzed, and a fusion feature phoneme recognition model based on prior text information is constructed to identify phonemes of speech uttered by speakers. This model includes an audio encoding module, a prior text encoding module, a feature fusion module, and fully connected layers. The model takes speech and its corresponding prior text as input and outputs a predicted phoneme sequence of the speech. The model recognizes accented speech as phonemes that do not match the transcribed phoneme sequence of the actual speech text and quantitatively evaluates the accents in ATC communication by calculating the differences between the recognized phoneme sequence and the transcribed phoneme sequence of the actual speech text. Additionally, different levels of accents are input into different types of speech recognition models to analyze and compare the recognition accuracy of the models. Result: Experimental results show that, under the same experimental conditions, the highest impact of different levels of accents on speech recognition accuracy in ATC communication is 26.37%. Discussion: This further demonstrates that accents affect the accuracy of speech recognition models in ATC communication and can be considered as one of the metrics for evaluating the quality of ATC speech.

[Analysis of effectiveness of one-hole split endoscopy technique in treatment of lumbar spinal stenosis].

Objective: To investigate the effectiveness of one-hole split endoscope (OSE) technique in the treatment of single segment lumbar spinal stenosis (LSS). Methods: The clinical data of 32 single segment LSS patients treated with OSE technique for simple spinal canal decompression between January 2022 and December 2022, who met the selection criteria, were retrospectively analysed. There were 18 males and 14 females, the age ranged from 45 to 82 years, with an average of 65.1 years. The disease duration was 9-72 months, with an average of 34.9 months. The surgical segments included L 3, 4 in 3 cases, L 4, 5 in 19 cases, and L 5, S 1 in 10 cases. The incision length, operation time, intraoperative blood loss, intraoperative radiation exposure frequency, postoperative mobilization time, and the area of the patient's lesion segment dural sac before operation and at 1 month after operation were recorded. Low back pain and leg pain were assessed by visual analogue scale (VAS) score before operation and at 3 days, 3 months, and 12 months after operation; functional recovery was assessed by Oswestry disability index (ODI) before operation and at 3 months and 12 months after operation; the effectiveness was assessed by modified MacNab criteria at last follow-up. Results: All 32 patients successfully completed the operation, with an average incision length of 2.05 cm, an average operation time of 88.59 minutes, an average intraoperative blood loss of 46.72 mL, an average intraoperative radiation exposure frequency of 3.84 times, and an average postoperative mobilization time of 11.66 hours. All patients were followed up 12-16 months, with an average of 13.5 months. One patient experienced lower limb numbness, pain, and decreased muscle strength after operation, while the remaining patients did not experience complications such as dural tear or important nerve damage. The VAS scores of low back pain and leg pain and ODI in patients at various time points after operation were significantly better than preoperative ones, and each indicator further improved with time. The differences between time points were significant ( P<0.05). At 1 month after operation, the area of the patient's lesion segment dural sac was (123.13±19.66) mm 2, which significantly increased compared to preoperative (51.25±9.50) mm 2 ( t=-18.616, P<0.001). At last follow-up, the improved MacNab criteria were used to evaluate the effectiveness, with 18 cases achieving excellent results, 11 cases being good, and 3 cases being fair, with an excellent and good rate of 90.6%. Conclusion: The effectiveness of using OSE technique for simple spinal canal decompression treatment of single segment LSS is satisfactory, with the advantages of minimal surgical trauma and fast recovery.

Identification of dynamic changes in volatile compounds and metabolites during the smoking process of Zhenba bacon by GC-IMS combined metabolomics.

Zhenba bacon is a traditional cured bacon product with a rich history that originated from Zhenba County, Shaanxi Province. This study aimed to investigate the patterns of volatile compound formation and changes in metabolites during the smoking process in Zhenba bacon. Firstly, the sensory properties and physicochemical properties of Zhenba bacon were analyzed. Gas chromatography-ion mobility spectrometry (GC-IMS) and nontargeted metabolomics technology were used to analyze Zhenba bacon from different smoking stages. The results show a gradual increase in the sensory acceptance and volatile flavor compounds such as aldehydes, ketones, and esters with the prolongation of smoking of Zhenba bacon. LC-MS analysis identified 191 co-expressed differentially metabolites, with amino acid and lipid metabolism being the main metabolic pathways according to KEGG enrichment analysis. Temporal expression analysis of bacon metabolites at each stage revealed a decrease in harmful steroid hormones such as cortisone and an increase in amino acids and lipid metabolites, such as arginine, lysine, acid, and cholesterol, that contribute to the flavor of bacon. In summary, duration of smoking increased, the amount of flavor substances in Zhenba bacon gradually increased, and the safety and quality of bacon reached the optimal level after 32 days of smoking. This study provides valuable insights into the dynamic changes in volatile flavor compounds in Zhenba bacon and establishes a theoretical foundation for quality control during its production.

Immunogenic cell death related mRNAs associated signature to predict immunotherapeutic response in osteosarcoma.

Background: Immunogenic cell death (ICD) is related to cancer prognosis, which has a synergic effect in combination with chemotherapy or immunotherapy. Yet, the relationship between ICD and osteosarcoma remained unclear. Materials and methods: Three osteosarcoma datasets including therapeutically applicable research to generate effective treatments (TARGET), GSE126209 and GSE21257 datasets were included. A protein-protein interaction network was constructed based on ICD-related genes. We performed unsupervised consensus clustering to classify molecular subtypes (clusters). Survival analysis, Estimation of stromal and immune cells in malignant tumour tissues using expression data (ESTIMATE), Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), and differential analysis were employed to characterize the molecular differences between different clusters. Univariate Cox regression analysis was conducted to confirm prognostic genes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to demonstrate the aberrant expression of ICD-correlated signature genes in osteosarcoma. A series of cellular experiments, including cell counting kit-8 (CCK-8), transwell, and flow cytometry, were used to demonstrate the regulatory role of key genes in the ICD model on the malignant phenotype of osteosarcoma. Results: Three clusters (cluster1, 2, 3) were constructed and they showed distinct overall survival and immune infiltration. ICD-related genes were highly expressed in cluster1. Moreover, Cluster1 had the best prognosis, high immune score and high expression of human leukocyte antigen (HLA)-related genes. TLR4, LY96, IFNGR1, CD4, and CASP1 were identified as prognostic genes for establishing an ICD-related risk signature. According to the risk signature, two risk groups (high and low risks) showing differential prognosis and response to immunotherapy. The low risks group had a better prognosis but was not sensitive to immunotherapy. Molecular assays verified that prognostic genes were abnormally under-expressed in osteosarcoma. Cellular assays demonstrated that LY96, the most significantly down-regulated gene in osteosarcoma, inhibited the migration, invasion, and proliferation phenotypes of osteosarcoma cells and prolonged the cell cycle. Analysis of oxidative stress related pathway enrichment in tumor microenvironment was conducted by single-sample gene set enrichment analysis (ssGSEA). Conclusions: This study demonstrated the prognostic significance of ICD-correlated genes in osteosarcoma patients. The five-gene risk signature facilitate prognostic evaluation and prediction of osteosarcoma patients' response to immunotherapy. The risk signature also offered a possibility for the exploit of novel ICD-related treatment.

Efficient learning of mixed-state tomography for photonic quantum walk.

Noise-enhanced applications in open quantum walk (QW) has recently seen a surge due to their ability to improve performance. However, verifying the success of open QW is challenging, as mixed-state tomography is a resource-intensive process, and implementing all required measurements is almost impossible due to various physical constraints. To address this challenge, we present a neural-network-based method for reconstructing mixed states with a high fidelity (∼97.5%) while costing only 50% of the number of measurements typically required for open discrete-time QW in one dimension. Our method uses a neural density operator that models the system and environment, followed by a generalized natural gradient descent procedure that significantly speeds up the training process. Moreover, we introduce a compact interferometric measurement device, improving the scalability of our photonic QW setup that enables experimental learning of mixed states. Our results demonstrate that highly expressive neural networks can serve as powerful alternatives to traditional state tomography.

[Adsorption Properties of Magnetic Phosphorous Camellia Oleifera Shells Biochar to Sulfamethoxazole in Water].

Magnetic phosphorous biochar （MPBC） was prepared from Camellia oleifera shells using phosphoric acid activation and iron co-deposition. The materials were characterized and analyzed through scanning electron microscopy （SEM）， X-ray diffractometry （XRD）， specific surface area and pore size analysis （BET）， Fourier infrared spectroscopy （FT-IR）， and X-ray photoelectron spectroscopy （XPS）. MPBC had a high surface area （1 139.28 m2·g-1） and abundant surface functional groups， and it could achieve fast solid-liquid separation under the action of an external magnetic field. The adsorption behavior and influencing factors of sulfamethoxazole （SMX） in water were investigated. The adsorbent showed excellent adsorption properties for SMX under acidic and neutral conditions， and alkaline conditions and the presence of CO32- had obvious inhibition on adsorption. The adsorption process conformed to the quasi-second-order kinetics and Langmuir model. The adsorption rate was fast， and the maximum adsorption capacity reached 356.49 mg·g-1. The adsorption process was a spontaneous exothermic reaction， and low temperature was beneficial to the adsorption. The adsorption mechanism was mainly the chemisorption of pyrophosphate surface functional groups （C-O-P bond） between the SMX molecule and MPBC and also included hydrogen bonding， π-π electron donor-acceptor （π-πEDA） interaction， and a pore filling effect. The development of MPBC adsorbent provides an effective way for resource utilization of waste Camellia oleifera shells and treatment of sulfamethoxazole wastewater.

Retinol dehydrogenase 12 (RDH12) knock out may cause hyperuricemia phenotype in mice.

Hyperuricemia is a chronic metabolic disease caused by purine metabolism disorder. And several gene loci and transporter proteins that associated with uric acid transport functions have been identified. Retinol Dehydrogenase 12 (RDH12), recognized for its role in safeguarding photoreceptors, and our study investigated the potential impact of Rdh12 mutations on other organs and diseases, particularly hyperuricemia. We assessed Rdh12 mRNA expression levels in various tissues and conducted serum biochemical analyses in Rdh12-/- mice. Compared with the wild type, significant alterations in serum uric acid levels and kidney-related biochemical indicators have been revealed. Then further analysis, including quantitative RT-PCR of gene expression in the liver and kidney, highlighted variations in the expression levels of specific genes linked to hyperuricemia. And renal histology assessment exposed mild pathological lesions in the kidneys of Rdh12-/- mice. In summary, our study suggests that Rdh12 mutations impact not only retinal function but also contribute to hyperuricemia and renal disease phenotypes in mice. Our finding implies that individuals with Rdh12 mutations may be prone to hyperuricemia and gout, emphasizing the significance of preventive measures and regular examinations in daily life.

Genetically supported causality between gut microbiota, immune cells and morphine tolerance: a two-sample Mendelian randomization study.

Background: Previous researches have suggested a significant connection between the gut microbiota/immune cells and morphine tolerance (MT), but there is still uncertainty regarding their causal relationship. Hence, our objective is to inverstigate this causal association and reveal the impact of gut microbiota/immune cells on the risk of developing MT using a two-sample Mendelian randomization (MR) study. Methods: We conducted a comprehensive analysis using genome-wide association study (GWAS) summary statistics for gut microbiota, immune cells, and MT. The main approach employed was the inverse variance-weighted (IVW) method in MR. To assess horizontal pleiotropy and remove outlier single-nucleotide polymorphisms (SNPs), we utilized the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) technique as well as MR-Egger regression. Heterogeneity detection was performed using Cochran's Q-test. Additionally, leave-one-out analysis was carried out to determine if any single SNP drove the causal association signals. Finally, we conducted a reverse MR to evaluate the potential of reverse causation. Results: We discovered that 6 gut microbial taxa and 16 immune cells were causally related to MT (p < 0.05). Among them, 2 bacterial features and 9 immunophenotypes retained a strong causal relationship with lower risk of MT: genus. Lachnospiraceae NK4A136group (OR: 0.962, 95% CI: 0.940-0.987, p = 0.030), genus. RuminococcaceaeUCG011 (OR: 0.960, 95% CI: 0.946-0.976, p = 0.003), BAFF-R on B cell (OR: 0.972, 95% CI: 0.947-0.998, p = 0.013). Furthermore, 4 bacterial features and 7 immunophenotypes were identified to be significantly associated with MT risk: genus. Flavonifractor (OR: 1.044, 95% CI: 1.017-1.069, p = 0.029), genus. Prevotella9 (OR: 1.054, 95% CI: 1.020-1.090, p = 0.037), B cell % CD3-lymphocyte (OR: 1.976, 95% CI: 1.027-1.129, p = 0.026). The Cochrane's Q test revealed no heterogeneity (p > 0.05). Furthermore, the MR-Egger and MR-PRESSO analyses reveal no instances of horizontal pleiotropy (p > 0.05). Besides, leave-one-out analysis confirmed the robustness of MR results. After adding BMI to the multivariate MR analysis, the gut microbial taxa and immune cells exposure-outcome effect were attenuated. Conclusion: Our research confirm the potential link between gut microbiota and immune cells with MT, shedding light on the mechanism by which gut microbiota and immune cells may contribute to MT. These findings lay the groundwork for future investigations into targeted prevention strategies.

Analysis of Epidemiological and Issues Encountered in Case Reports on Echinococcosis - China, 2022.

What is already known about this topic?: Echinococcosis is classified as a Class C infectious disease in China. It is endemic in 370 counties located in the agricultural and pastoral regions of western China. What is added by this report?: This report provides a comprehensive overview of the cases of echinococcosis reported in China in 2022. Following a thorough evaluation conducted by provincial CDCs, it was identified that 105 new cases were not reported through the National Notifiable Disease Reporting System. Furthermore, there were 1,051 cases that were reported among patients who had been previously diagnosed with echinococcosis. What are the implications for public health practice?: The reported cases of echinococcosis in non-endemic counties of provincial-level administrative divisions where the disease is endemic need to be given more attention, as there is a potential risk of it spreading within the non-endemic areas. Inadequate reporting practices by clinical medical institutions are hindering the subsequent investigations carried out by CDCs. It is important to implement enhanced health promotion efforts that focus on high-risk populations to address unhealthy lifestyles.