Development and validation of a nomogram to predict acute postoperative urinary retention in ischemic stroke patients following femoral artery puncture.

Background: Acute postoperative urinary retention (POUR) is a common complication in patients with ischemic stroke following femoral artery puncture (FAP), leading to discomfort, delayed hospital discharge, and increased patient morbidity. The relevant risk factors are unclear; thus, a predictive tool is required to guide treatment decisions. Objective: To develop and validate a nomogram to predict acute POUR in patients with ischemic stroke following FAP. Methods: We retrospectively collected cases from 1729 patients with ischemic stroke from the electronic record system of Jiangmen Central Hospital from January 2021 to December 2023. A total of 731 patients were randomly divided into development (n = 511, 70%) and validation (n = 220, 30%) groups. Univariate and multivariate logistic regression analyses with backward stepwise regression were used to select the predictive variables, and a nomogram was developed. The discrimination was evaluated based on the area under the curve (AUC). Calibration was assessed using calibration plots and the Hosmer-Lemeshow test. Clinical applications were evaluated using decision curve analysis (DCA). Results: The incidence of acute POUR was 12.72%. Preoperative statin use within 24 h, operation type, intraoperative infusion, postoperative water intake within 3 h, postoperative pain, and postoperative anxiety were included in the nomogram. The AUC values were 0.764 [95% confidence interval (CI): 0.705-0.825] in the development group and 0.741 (95% CI: 0.615-0.856) in the validation group. The calibration plots showed good calibration. The p values in the Hosmer-Lemeshow tests were 0.962 and 0.315 for the development and validation groups, respectively. The DCA showed that patients could benefit from this nomogram. Conclusion: A nomogram was developed to successfully predict acute POUR in patients with ischemic stroke following FAP. This nomogram is a convenient and effective tool for clinicians to aid in the prevention and early intervention of acute POUR.

Regulating V2O5 Layer Spacing by a Polyaniline Molecule Chain to Improve Electrochemical Performance in Salinity Gradient Energy Conversion.

Salinity gradient energy is a chemical potential energy between two solutions with different ionic concentrations, which is also an ocean energy at the junction of rivers and seas. In our original work, the device "activated carbon//(0.083 M Na2SO4, 0.5 M Na2SO4)//vanadium pentoxide" for the conversion of salinity gradient energy was designed, and the conversion value of 6.29 J g-1 was obtained. However, the low specific surface area of the original V2O5 inevitably resulted in limited active sites and slow ionic transport rates, and the inherent lower conductivity and narrower layer spacing of the original V2O5 also resulted in poor electrode kinetic performance and cycle stability, hindering its practical application. To solve the above problems, the present work provides a strategy of using polyaniline (PANI) molecule chain intercalation to regulate the layer spacing of the original V2O5, and through the expansion and traction of the layer spacing, the composite PANI/V2O5 (PVO) with high specific surface area is prepared and used as an anode material for electrochemical conversion of salinity gradient energy application. The significantly increased layer spacing of the crystal plane (001) corresponding to the original V2O5 was confirmed with the PANI by the hydrogen bonding and the van der Waals force. The high specific surface area of the composite provides more electrochemical active sites to realize a fast Na+ migration rate and high specific capacitance. Meanwhile, the inserted PANI molecule chain, which acts not only as a pillar enlarging the Na+ diffusion channel but also as an anchor locking the gap between V2O5 bilayers, improves the structural stability of the V2O5 electrode during the electrochemical conversion process. The proposed insertion strategy for the conductive polymer PANI has created a new way to improve the cycle stability performance of the salinity gradient energy conversion device.

Cross-institutional evaluation of deep learning and radiomics models in predicting microvascular invasion in hepatocellular carcinoma: validity, robustness, and ultrasound modality efficacy comparison.

PURPOSE: To conduct a head-to-head comparison between deep learning (DL) and radiomics models across institutions for predicting microvascular invasion (MVI) in hepatocellular carcinoma (HCC) and to investigate the model robustness and generalizability through rigorous internal and external validation. METHODS: This retrospective study included 2304 preoperative images of 576 HCC lesions from two centers, with MVI status determined by postoperative histopathology. We developed DL and radiomics models for predicting the presence of MVI using B-mode ultrasound, contrast-enhanced ultrasound (CEUS) at the arterial, portal, and delayed phases, and a combined modality (B + CEUS). For radiomics, we constructed models with enlarged vs. original regions of interest (ROIs). A cross-validation approach was performed by training models on one center's dataset and validating the other, and vice versa. This allowed assessment of the validity of different ultrasound modalities and the cross-center robustness of the models. The optimal model combined with alpha-fetoprotein (AFP) was also validated. The head-to-head comparison was based on the area under the receiver operating characteristic curve (AUC). RESULTS: Thirteen DL models and 25 radiomics models using different ultrasound modalities were constructed and compared. B + CEUS was the optimal modality for both DL and radiomics models. The DL model achieved AUCs of 0.802-0.818 internally and 0.667-0.688 externally across the two centers, whereas radiomics achieved AUCs of 0.749-0.869 internally and 0.646-0.697 externally. The radiomics models showed overall improvement with enlarged ROIs (P < 0.05 for both CEUS and B + CEUS modalities). The DL models showed good cross-institutional robustness (P > 0.05 for all modalities, 1.6-2.1% differences in AUC for the optimal modality), whereas the radiomics models had relatively limited robustness across the two centers (12% drop-off in AUC for the optimal modality). Adding AFP improved the DL models (P < 0.05 externally) and well maintained the robustness, but did not benefit the radiomics model (P > 0.05). CONCLUSION: Cross-institutional validation indicated that DL demonstrated better robustness than radiomics for preoperative MVI prediction in patients with HCC, representing a promising solution to non-standardized ultrasound examination procedures.

Spatial transcriptomics of fetal membrane-Decidual interface reveals unique contributions by cell types in term and preterm births.

During pregnancy, two fetomaternal interfaces, the placenta-decidua basalis and the fetal membrane-decidua parietals, allow for fetal growth and maturation and fetal-maternal crosstalk, and protect the fetus from infectious and inflammatory signaling that could lead to adverse pregnancy outcomes. While the placenta has been studied extensively, the fetal membranes have been understudied, even though they play critical roles in pregnancy maintenance and the initiation of term or preterm parturition. Fetal membrane dysfunction has been associated with spontaneous preterm birth (PTB, < 37 weeks gestation) and preterm prelabor rupture of the membranes (PPROM), which is a disease of the fetal membranes. However, it is unknown how the individual layers of the fetal membrane decidual interface (the amnion epithelium [AEC], the amnion mesenchyme [AMC], the chorion [CTC], and the decidua [DEC]) contribute to these pregnancy outcomes. In this study, we used a single-cell transcriptomics approach to unravel the transcriptomics network at spatial levels to discern the contributions of each layer of the fetal membranes and the adjoining maternal decidua during the following conditions: scheduled caesarian section (term not in labor [TNIL]; n = 4), vaginal term in labor (TIL; n = 3), preterm labor with and without rupture of membranes (PPROM; n = 3; and PTB; n = 3). The data included 18,815 genes from 13 patients (including TIL, PTB, PPROM, and TNIL) expressed across the four layers. After quality control, there were 11,921 genes and 44 samples. The data were processed by two pipelines: one by hierarchical clustering the combined cases and the other to evaluate heterogeneity within the cases. Our visual analytical approach revealed spatially recognized differentially expressed genes that aligned with four gene clusters. Cluster 1 genes were present predominantly in DECs and Cluster 3 centered around CTC genes in all labor phenotypes. Cluster 2 genes were predominantly found in AECs in PPROM and PTB, while Cluster 4 contained AMC and CTC genes identified in term labor cases. We identified the top 10 differentially expressed genes and their connected pathways (kinase activation, NF-κB, inflammation, cytoskeletal remodeling, and hormone regulation) per cluster in each tissue layer. An in-depth understanding of the involvement of each system and cell layer may help provide targeted and tailored interventions to reduce the risk of PTB.

HIF-1α protects nucleus pulposus cells from oxidative stress-induced mitochondrial impairment through PDK-1.

The pathogenesis of intervertebral disc degeneration (IVDD) involves complex signaling networks and various effector molecules, and our understanding of the pathogenesis of IVDD is limited. Hypoxia inducible factor-1α (HIF-1α) is closely related to IVDD, and there is excessive oxidative stress concurrent with IVDD. In this study, we found that HIF-1α could protect nucleus pulposus cells from excessive oxidative stress by reversing the imbalance between oxidants and antioxidants and thus mitigating the oxidative stress-induced mitochondrial impairment. With further exploration, we found that pyruvate dehydrogenase kinase 1 (PDK-1) was involved in the protective effect of HIF-1α on nucleus pulposus cells under oxidative stress. We suggested that HIF-1α could preserve the mitochondrial integrity and activate glycolysis in nucleus pulposus cells via PDK-1, and the addition of DCA, a PDK-1 inhibitor, could blunt the protective effect of HIF-1α. In addition, the HIF-1α/PDK-1 regulatory axis was also confirmed in vivo through HIF-1α knockout mice model. Therefore, we propose that HIF-1α protects nucleus pulposus cells from excessive oxidative stress by maintaining the mitochondrial integrity and glycolysis via PDK-1, thus enriching the insight into the protective mechanism of HIF-1α against IVDD, and providing a novel therapeutic target for the treatment of IVDD.

Integrated Bioinformatic Analysis Reveals the Oncogenic, Survival, and Prognostic Characteristics of TPX2 in Hepatocellular Carcinoma.

Targeting protein for Xenopus kinesin-like protein 2 (TPX2), a well-known mitotic protein, has been linked to carcinogenesis in several cancers. This study investigated the role of TPX2 in hepatocellular carcinoma (HCC) from various aspects using bioinformatic analyses. TPX2 expression and its prognostic value in pan-cancers were analyzed using SangerBox. TPX2 expression and its association with prognosis, immune infiltration, tumor mutations, and signaling pathways in HCC were analyzed using UALCAN, BoxKaplan-Meier Plotter, GEPIA, Human Protein Atlas, TIMER 2.0, and SangerBox. Genes co-expressed with TPX2 in HCC were analyzed using the HCCDB database, followed by functional enrichment using SangerBox. Clinical predictive models were established based on TPX2 and its co-expressed genes using the ACLBI database. TPX2 expression significantly increased in pan-cancers and was associated with survival in nearly half of the cancer types. High TPX2 expression has been linked to poor survival outcomes in patients with HCC. TPX2 expression was positively correlated with abundant infiltration of immune cells (including B cells, CD4 + /CD8 + T cells, macrophages, neutrophils, and dendritic cells), TP53 mutation, and carcinogenesis-related pathways, such as the PI3K/AKT/mTOR pathway, cellular response to hypoxia, and tumor proliferation signature. Nineteen genes were found to be co-expressed with TPX2 in HCC, and these genes showed close positive correlations and were mainly implicated in cell cycle-related functions. A prognostic model established using TPX2 and its expressed genes could stratify HCC patients into high- and low-risk groups, with a significantly shorter survival time in high-risk groups. The prognostic model performed well in predicting 1-, 3-, and 5-year survival of patients with HCC, with areas under the curve of 0.801, 0.725, and 0.711, respectively. TPX2 functions as an oncogene in HCC, and its high expression is detrimental to the survival of patients with HCC. Thus, TPX2 may be a prognostic biomarker and potential therapeutic target for HCC.

TRIM33 enhances the ubiquitination of TFRC to enhance the susceptibility of liver cancer cells to ferroptosis.

BACKGROUND: Hepatocellular carcinoma (HCC) is a common malignancy, and ferroptosis is a novel form of cell death driven by excessive lipid peroxidation. In recent years, ferroptosis has been widely utilized in cancer treatment, and the ubiquitination modification system has been recognized to play a crucial role in tumorigenesis and metastasis. Increasing evidence suggests that ubiquitin regulates ferroptosis-related substrates involved in this process. However, the precise mechanism of utilizing ubiquitination modification to regulate ferroptosis for HCC treatment remains unclear. METHODS: In this study, we detected the expression of TRIM33 in HCC using immunohistochemistry and western blotting techniques. The functional role of TRIM33 was verified through both in vitro and in vivo experiments. To evaluate the level of ferroptosis, mitochondrial superoxide levels, MDA levels, Fe2+ levels, and cell viability were assessed. Downstream substrates of TRIM33 were screened and confirmed via immunoprecipitation, immunofluorescence staining, and ubiquitination modification experiments. RESULTS: Our findings demonstrate that TRIM33 inhibits the growth and metastasis of HCC cells both in vitro and in vivo while promoting their susceptibility to ferroptosis. Mechanistically speaking, TRIM33 induces cellular ferroptosis through E3 ligase-dependent degradation of TFRC-a known inhibitor of this process-thus elucidating the specific type and site at which TFRC undergoes modification by TRIM33. CONCLUSION: In summary, our study reveals an important role for TRIM33 in HCC treatment while providing mechanistic support for its function. Additionally highlighted is the significance of ubiquitination modification leading to TFRC degradation-an insight that may prove valuable for future targeted therapies.

A 14-amino acid cationic peptide Bolespleenin334-347 from the marine fish mudskipper Boleophthalmus pectinirostris exhibiting potent antimicrobial activity and therapeutic potential.

Antimicrobial peptides (AMPs) are an important component of innate immunity in both vertebrates and invertebrates, and some of the unique characteristics of AMPs are usually associated with their living environment. The marine fish, mudskipper Boleophthalmus pectinirostris, usually live amphibiously in intertidal environments that are quite different from other fish species, which would be an exceptional source of new AMPs. In the study, an AMP named Bolespleenin334-347 was identified, which was a truncated peptide derived from a new functional gene found in B. pectinirostris, that was up-regulated in response to bacterial challenge. Bolespleenin334-347 had only 14 amino acid residues, including five consecutive arginine residues. It was found that the peptide had broad-spectrum antibacterial activity, good thermal stability and sodium ion tolerance. Bolespleenin334-347 killed Acinetobacter baumannii and Staphylococcus aureus by disrupting the structural integrity of the bacterial membrane, leading to leakage of the cellular contents, and inducing accumulation of bacterial endogenous reactive oxygen species (ROS). In addition, Bolespleenin334-347 effectively inhibited biofilm formation of A. baumannii and S. aureus and long-term treatment did not lead to the development of resistance. Importantly, Bolespleenin334-347 maintained stable activity against clinically multi-drug resistant bacterial strains. In addition, it was noteworthy that Bolespleenin334-347 showed superior efficacy to LL-37 and vancomycin in a constructed mouse model of MRSA-induced superficial skin infections, as evidenced by a significant reduction in bacterial load and more favorable wound healing. This study provides an effective antimicrobial agent for topical skin infections with potential therapeutic efficacy for infections with drug-resistant bacteria, including MRSA.

The effects of sensorial and mobility frailty on the overall and domain-specific cognition performance of Chinese community-dwelling older adults.

This study aimed to investigate the different impacts of sensorial and mobility frailty on overall and domain-specific cognitive function. Further, the independent associations between other intricate capacity (IC) dimensions, including vitality and psychological dimensions, and overall and domain-specific cognitive function were investigated. A total of 429 participants (mean age, 72.91 ±â€…7.014 years; 57.30% female) underwent IC capacity assessment. Other covariates, such as demographics, health-related variables were also assessed. Overall or domain-specific cognitive impairment was used as a dependent variable in logistic regression analyses adjusted for demographic, health-related, and psychosocial confounders. After adjustment for demographic, health-related, and psychosocial confounders, individuals with sensorial frailty (odds ratio [OR] = 0.435; 95% confidence interval [CI] = 0.236-0.801; P = .008) had a significantly lower risk of mild cognitive impairment (MCI), marginally low delayed memory impairment (OR = 0.601, 95% CI = 0.347-1.040; P = .069), and language impairment (OR = 0.534, 95% CI = 0.305-0.936; OR = 0.318, P = .029; OR = 0.318,95% CI = 0.173-0.586; P < .001) by Boston naming and animal fluency tests than did those with both sensorial and mobility frailty or mobility frailty only. Depressive symptoms had a significant negative influence on executive function. Cardiovascular disease and non-skin malignancy were independent determinants of MCI, and diabetes mellitus was independently associated with processing speed, attention, and executive function. Sensorial and mobility frailty were independent risk factors for cognitive impairment. Mobility frailty had a greater negative influence on the overall cognitive function and memory and language function than did sensorial frailty. The reserve decline in the psychological dimension of IC and chronic diseases also had a significant adverse influence on overall and domain-specific cognition function.

Ultrathin BiOCl-OV/CoAl-LDH S-scheme heterojunction for efficient photocatalytic peroxymonosulfate activation to boost Co (IV)=O generation.

Sustainable and rapid production of high-valent cobalt-oxo (Co(IV)=O) species for efficiently removing organic pollutants is challenging in permoxymonosulfate (PMS) based advanced-oxidation-processes (AOPs) due to the limitation of the high 3d-orbital electronic occupancy of Co and slow conversion from Co(III) to Co(II). Herein, S-scheme BiOCl-OV/CoAl-LDH heterojunction were constructed by ultrathin BiOCl with the oxygen-vacancy (OV) self-assembled with ultrathin CoAl-LDH. OV promoted the formation of charge transfer channel (Bi-O-Co bonds) at the interface of the heterojunction and reduced electron occupation of the Co 3d-orbital to facilitate the generation of Co(IV)=O in the BiOCl-OV/CoAl-LDH/PMS/Visible-light system. S-scheme heterojunction accelerated the photogenerated electrons to allow rapid conversion of Co(III) to Co(II), promoting the fast two-electron transfer from Co(II) to Co(IV)=O. Consequently, the developed BiOCl-OV/CoAl-LDH/PMS/Visible-light system showed excellent degradation efficiency for most of organic pollutions, and exhibited very high removal capability for the actual industrial wastewater. This study provides a new insight into the evolution of Co(IV)=O and the coordinative mechanism for photocatalysis and PMS activation.

Causal relationship between air pollution, lung function, gastroesophageal reflux disease, and non-alcoholic fatty liver disease: univariate and multivariate Mendelian randomization study.

Background: The association between air pollution, lung function, gastroesophageal reflux disease, and Non-alcoholic fatty liver disease (NAFLD) remains inconclusive. Previous studies were not convincing due to confounding factors and reverse causality. We aim to investigate the causal relationship between air pollution, lung function, gastroesophageal reflux disease, and NAFLD using Mendelian randomization analysis. Methods: In this study, univariate Mendelian randomization analysis was conducted first. Subsequently, Steiger testing was performed to exclude the possibility of reverse association. Finally, significant risk factors identified from the univariate Mendelian analysis, as well as important factors affecting NAFLD from previous observational studies (type 2 diabetes and body mass index), were included in the multivariable Mendelian randomization analysis. Results: The results of the univariable Mendelian randomization analysis showed a positive correlation between particulate matter 2.5, gastroesophageal reflux disease, and NAFLD. There was a negative correlation between forced expiratory volume in 1 s, forced vital capacity, and NAFLD. The multivariable Mendelian randomization analysis indicated a direct causal relationship between gastroesophageal reflux disease (OR = 1.537, p = 0.011), type 2 diabetes (OR = 1.261, p < 0.001), and NAFLD. Conclusion: This Mendelian randomization study confirmed the causal relationships between air pollution, lung function, gastroesophageal reflux, and NAFLD. Furthermore, gastroesophageal reflux and type 2 diabetes were identified as independent risk factors for NAFLD, having a direct causal connection with the occurrence of NAFLD.

Combined Machine Learning and High-Throughput Calculations Predict Heyd-Scuseria-Ernzerhof Band Gap of 2D Materials and Potential MoSi2N4 Heterostructures.

We present a novel target-driven methodology devised to predict the Heyd-Scuseria-Ernzerhof (HSE) band gap of two-dimensional (2D) materials leveraging the comprehensive C2DB database. This innovative approach integrates machine learning and density functional theory (DFT) calculations to predict the HSE band gap, conduction band minimum (CBM), and valence band maximum (VBM) of 2176 types of 2D materials. Subsequently, we collected a comprehensive data set comprising 3539 types of 2D materials, each characterized by its HSE band gaps, CBM, and VBM. Considering the lattice disparities between MoSi2N4 (MSN) and 2D materials, our analysis predicted 766 potential MSN/2D heterostructures. These heterostructures are further categorized into four distinct types based on the relative positions of their CBM and VBM: Type I encompasses 230 variants, Type II comprises 244 configurations, Type III consists of 284 permutations, and 0 band gap comprises 8 types.

CT-derived Radiomics Predicts the Efficacy of Tyrosine Kinase Inhibitors in Osteosarcoma Patients with Pulmonary Metastasis.

BACKGROUND: To construct and validate the CT-based radiomics model for predicting the tyrosine kinase inhibitors (TKIs) effects in osteosarcoma (OS) patients with pulmonary metastasis. METHODS: OS patients with pulmonary metastasis treated with TKIs were randomly separated into training and testing cohorts (2:1 ratio). Radiomic features were extracted from the baseline unenhanced chest CT images. The random survival forest (RSF) and Kaplan-Meier survival analyses were performed to construct and evaluate radiomics signatures (R-model-derived). The univariant and multivariant Cox regression analyses were conducted to establish clinical (C-model) and combined models (RC-model). The discrimination abilities, goodness of fit and clinical benefits of the three models were assessed and validated in both training and testing cohorts. RESULTS: A total of 90 patients, 57 men and 33 women, with a mean age of 18 years and median progression-free survival (PFS) of 7.2 months, were enrolled. The R-model was developed with nine radiomic features and demonstrated significant predictive and prognostic values. In both training and testing cohorts, the time-dependent area under the receiver operating characteristic curves (AUC) of the R-model and RC-model exhibited obvious superiority over C-model. The calibration and decision curve analysis (DCA) curves indicated that the accuracy of the R-model was comparable to RC-model, which exhibited significantly better performance than C-model. CONCLUSIONS: The R-model showed promising potential as a predictor for TKI responses in OS patients with pulmonary metastasis. It can potentially identify pulmonary metastatic OS patients most likely to benefit from TKIs treatment and help guide optimized clinical decisions.

Understanding and exploring the diversity of soil microorganisms in tea (Camellia sinensis) gardens: toward sustainable tea production.

Leaves of Camellia sinensis plants are used to produce tea, one of the most consumed beverages worldwide, containing a wide variety of bioactive compounds that help to promote human health. Tea cultivation is economically important, and its sustainable production can have significant consequences in providing agricultural opportunities and lowering extreme poverty. Soil parameters are well known to affect the quality of the resultant leaves and consequently, the understanding of the diversity and functions of soil microorganisms in tea gardens will provide insight to harnessing soil microbial communities to improve tea yield and quality. Current analyses indicate that tea garden soils possess a rich composition of diverse microorganisms (bacteria and fungi) of which the bacterial Proteobacteria, Actinobacteria, Acidobacteria, Firmicutes and Chloroflexi and fungal Ascomycota, Basidiomycota, Glomeromycota are the prominent groups. When optimized, these microbes' function in keeping garden soil ecosystems balanced by acting on nutrient cycling processes, biofertilizers, biocontrol of pests and pathogens, and bioremediation of persistent organic chemicals. Here, we summarize research on the activities of (tea garden) soil microorganisms as biofertilizers, biological control agents and as bioremediators to improve soil health and consequently, tea yield and quality, focusing mainly on bacterial and fungal members. Recent advances in molecular techniques that characterize the diverse microorganisms in tea gardens are examined. In terms of viruses there is a paucity of information regarding any beneficial functions of soil viruses in tea gardens, although in some instances insect pathogenic viruses have been used to control tea pests. The potential of soil microorganisms is reported here, as well as recent techniques used to study microbial diversity and their genetic manipulation, aimed at improving the yield and quality of tea plants for sustainable production.

Surface plasmon enhancement in silver nanowires and bilayer two-dimensional materials.

In order to improve the low light absorption of two-dimensional (2D) transition metal dichalcogenides (TMDCs), surface plasmon (SP) nanostructures have been widely studied. However, the impact of interlayer twist on such nanostructures has rarely been studied. Here, we construct two different composite structures of silver nanowires (Ag NWs) and pristine bilayer MoS2 (pBLM) or twisted bilayer MoS2 (tBLM). The interlayer twist can further promote the light utilization of MoS2, resulting in an ∼4-fold higher spectral enhancement in Ag/tBLM than that in Ag/pBLM. In addition, the photocurrent and detectivity of the phototransistor based on the Ag/tBLM composite structure were improved by 7-fold and ∼100-fold, respectively, compared to those of the Ag/pBLM phototransistor. Theoretical simulations show that the enhancement of photocurrent can be attributed to the enhancement of the local electric field at the interface between Ag NWs and the tBLM film, which is called the 'hot spot'. These results provide a reference for understanding the modulation mechanism of SPs and interlayer twist on the optoelectronic properties of 2D materials.

Three New Species of Russulaceae (Russulales, Basidiomycota) from Southern China.

The characterization of natural fungal diversity impacts our understanding of ecological and evolutionary processes and can lead to novel bioproduct discovery. Russula and Lactarius, both in the order Russulales, represent two large genera of ectomycorrhizal fungi that include edible as well as toxic varieties. Based on morphological and phylogenetic analyses, including nucleotide sequences of the internal transcribed spacer (ITS), the 28S large subunit of ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), the ribosomal mitochondrial small subunit (mtSSU), and the translation elongation factor 1-α (TEF1-α) gene sequences, we here describe and illustrate two new species of Russula and one new species of Lactarius from southern China. These three new species are: R. junzifengensis (R. subsect. Virescentinae), R. zonatus (R. subsect. Crassotunicatae), and L. jianyangensis (L. subsect. Zonarii).

Reduced recurrence rate and comparable functionality after wide resection and reverse total shoulder arthroplasty with allograft-prosthetic composite versus curettage for proximal humeral giant cell tumor: a multicenter retrospective study.

BACKGROUND: Giant cell tumors of bone (GCTBs) are rare, aggressive tumors, and the proximal humerus is a relatively rare location for GCTBs; limited evidence exists on which surgical approaches and reconstruction techniques are optimal. In the largest case series to date, we evaluated the recurrence rate of proximal humeral GCTBs and the functional outcomes of different resection and reconstruction options in this multicenter study. METHODS: All 51 patients included in this study received initial surgical treatment for proximal humeral GCTBs from January 2007 to December 2020, with a minimum 2-year follow-up period. Local recurrence and functional outcomes were statistically analyzed in relation to demographic, clinical, and primary surgical variables. Functional outcomes were reported by patients and were assessed by the Musculoskeletal Tumor Society score and QuickDASH instrument (shortened version of the Disabilities of the Arm, Shoulder and Hand instrument). RESULTS: The mean follow-up period was 81.5 months (range, 30-191 months), and the overall recurrence rate was 17.6% (9 of 51 patients). The majority of recurrences (n = 7) occurred in the first 2 years of follow-up. The intralesional curettage group (n = 23) showed a statistically significant difference in the recurrence rate compared with the en bloc resection group (n = 28) (34.8% vs. 3.6%, P = .007). Among shoulders receiving en bloc resection, 16 were reconstructed with hemiarthroplasty; 8, reverse total shoulder arthroplasty (rTSA) with allograft-prosthetic composite (APC) reconstruction; and 4, arthrodesis. On the basis of intention-to-treat analysis, the mean functional Musculoskeletal Tumor Society scores of the groups undergoing curettage, rTSA with APC, hemiarthroplasty, and arthrodesis were 26.0 ± 3.1, 26.0 ± 1.7, 20.3 ± 2.8, and 22.5 ± 1.3, respectively (P < .001 [with P < .001 for curettage vs. hemiarthroplasty and P = .004 for rTSA with APC vs. hemiarthroplasty]) and the mean QuickDASH scores were 14.0 ± 11.0, 11.6 ± 4.5, 33.1 ± 11.8, and 21.6 ± 4.7, respectively (P < .001 [with P < .001 for curettage vs. hemiarthroplasty and P = .003 for rTSA with APC vs. hemiarthroplasty]). CONCLUSIONS: On the basis of our data, en bloc resection followed by reverse shoulder arthroplasty showed a lower recurrence rate and no significant difference in functional outcome scores for proximal humeral GCTBs compared with intralesional curettage. Therefore, we believe that rTSA with APC may be reasonable for the initial treatment of proximal humeral GCTBs.

Achieving Molecular-Level Selective Detection of Volatile Organic Compounds through a Strong Coupling Effect of Ultrathin Nanosheets and Au Nanoparticles.

The high density of surface active sites, high efficiency of interfacial carrier transport, and molecular diffusion path determine the efficiency of the electrochemical sensors. The ultrathin structures have atomic-level thickness, carrier migration and heat diffusion are limited in the two-dimensional plane, resulting in excellent conductivity and high carrier concentration. A one-step chemical method is applied to synthesize defect-rich Au-SnO2 in an ultrathin nanosheet form (thickness of 2-3 nm). The strong interaction between Au and SnO2 via the Au-O-Sn bonding and the catalytic effect of Au can prolong the service life via decreasing the optimal operating temperature (55 °C) and promote the Au-SnO2 sensor to exclusively detect formaldehyde at the ppb level (300 ppb). The experimental findings along with theoretical study reveal that Au nanoparticles have a different effect on the competitive adsorption and chemical reaction over the surface of the Au-SnO2 with formaldehyde and other interfering VOC gases, such as methanol, ethanol, and acetone. This study provides mechanistic insights into the correlation between operating temperature and the performance of the Au-SnO2 chemiresistive sensor. This work allows the development of highly efficient and stable electrochemical sensors to detect VOC gases at room temperature in the future.

Dynamic nomogram for predicting hungry bone syndrome before parathyroidectomy.

PURPOSE: The objective of this study was to develop a dependable and uncomplicated prediction model utilizing clinical information readily accessible to patients before surgery. This model aimed to assess the likelihood of hungry bone syndrome occurrence in post-surgery patients with secondary hyperparathyroidism (SHPT), and to assist clinicians in adjusting treatment plans promptly. METHODS: In this study, we constructed an online nomogram utilizing independent variables determined through multiple logistic regression to predict the probability of HBS occurrence after parathyroidectomy in patients with secondary hyperparathyroidism. To evaluate the precision and dependability of the nomogram, we used receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: Multivariate logistic regression analyses on 136 eligible patients identified age, parathyroid hormone (PTH), and blood calcium as independent HBS risk factors, which were then integrated into the nomogram. The area under ROC curve demonstrated the nomogram's strong predictive accuracy. The calibration curve demonstrates consistency between the model's prediction probability and observed probability, reflecting high prediction accuracy of the nomogram. Dynamic nomograms were found to hold significant practical clinical value as demonstrated by clinical decision analysis. It can be accessed on https://min115.shinyapps.io/dynnomapp/ . CONCLUSION: In patients with secondary hyperparathyroidism, the dynamic nomogram based on age, parathyroid hormone, and blood calcium can more accurately predict the likelihood of HBS after parathyroidectomy, allowing doctors to make clinical decisions more quickly and adjust treatment plans in a timely manner to reduce the incidence of HBS.

Implications of ultrasound-based deep learning model for preoperatively differentiating combined hepatocellular-cholangiocarcinoma from hepatocellular carcinoma and intrahepatic cholangiocarcinoma.

OBJECTIVES: The current study developed an ultrasound-based deep learning model to make preoperative differentiation among hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma (cHCC-ICC). METHODS: The B-mode ultrasound images of 465 patients with primary liver cancer were enrolled in model construction, comprising 264 HCCs, 105 ICCs, and 96 cHCC-ICCs, of which 50 cases were randomly selected to form an independent test cohort, and the rest of study population was assigned to a training and validation cohorts at the ratio of 4:1. Four deep learning models (Resnet18, MobileNet, DenseNet121, and Inception V3) were constructed, and the fivefold cross-validation was adopted to train and validate the performance of these models. The following indexes were calculated to determine the differential diagnosis performance of the models, including sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), F-1 score, and area under the receiver operating characteristic curve (AUC) based on images in the independent test cohort. RESULTS: Based on the fivefold cross-validation, the Resnet18 outperformed other models in terms of accuracy and robustness, with the overall training and validation accuracy as 99.73% (± 0.07%) and 99.35% (± 0.53%), respectively. Furthers validation based on the independent test cohort suggested that Resnet 18 yielded the best diagnostic performance in identifying HCC, ICC, and cHCC-ICC, with the sensitivity, specificity, accuracy, PPV, NPV, F1-score, and AUC of 84.59%, 92.65%, 86.00%, 85.82%, 92.99%, 92.37%, 85.07%, and 0.9237 (95% CI 0.8633, 0.9840). CONCLUSION: Ultrasound-based deep learning algorithm appeared a promising diagnostic method for identifying cHCC-ICC, HCC, and ICC, which might play a role in clinical decision making and evaluation of prognosis.