Early identification of stroke through deep learning with multi-modal human speech and movement data.

JOURNAL/nrgr/04.03/01300535-202501000-00031/figure1/v/2024-05-14T021156Z/r/image-tiff Early identification and treatment of stroke can greatly improve patient outcomes and quality of life. Although clinical tests such as the Cincinnati Pre-hospital Stroke Scale (CPSS) and the Face Arm Speech Test (FAST) are commonly used for stroke screening, accurate administration is dependent on specialized training. In this study, we proposed a novel multimodal deep learning approach, based on the FAST, for assessing suspected stroke patients exhibiting symptoms such as limb weakness, facial paresis, and speech disorders in acute settings. We collected a dataset comprising videos and audio recordings of emergency room patients performing designated limb movements, facial expressions, and speech tests based on the FAST. We compared the constructed deep learning model, which was designed to process multi-modal datasets, with six prior models that achieved good action classification performance, including the I3D, SlowFast, X3D, TPN, TimeSformer, and MViT. We found that the findings of our deep learning model had a higher clinical value compared with the other approaches. Moreover, the multi-modal model outperformed its single-module variants, highlighting the benefit of utilizing multiple types of patient data, such as action videos and speech audio. These results indicate that a multi-modal deep learning model combined with the FAST could greatly improve the accuracy and sensitivity of early stroke identification of stroke, thus providing a practical and powerful tool for assessing stroke patients in an emergency clinical setting.

Engineering Core/Ligands Interfacial Anchors of Nanoparticles for Efficiently Inhibiting Both Aß and Amylin Fibrillization.

Accurate construction of artificial nano-chaperones' structure is crucial for precise regulation of protein conformational transformation, facilitating effective treatment of proteopathy. However, how the ligand-anchors of nano-chaperones affect the spatial conformational changes in proteins remains unclear, limiting the development of efficient nano-chaperones. In this study, three types of gold nanoparticles (AuNPs) with different core/ligands interface anchor structures (Au─NH─R, Au─S─R, and Au─C≡C─R, R = benzoic acid) are synthesized as an ideal model to investigate the effect of interfacial anchors on Aß and amylin fibrillization. Computational results revealed that the distinct interfacial anchors imparted diverse distributions of electrostatic potential on the nanointerface and core/ligands bond strength of AuNPs, leading to differential interactions with amyloid peptides. Experimental results demonstrated that all three types of AuNPs exhibit site-specific inhibitory effects on Aß40 fibrillization due to preferential binding. For amylin, amino-anchored AuNPs demonstrate strong adsorption to multiple sites on amylin and effectively inhibit fibrillization. Conversely, thiol- and alkyne-anchored AuNPs adsorb at the head region of amylin, promoting folding and fibrillization. This study not only provided molecular insights into how core/ligands interfacial anchors of nanomaterials induce spatial conformational changes in amyloid peptides but also offered guidance for precisely engineering artificial-chaperones' nanointerfaces to regulate the conformational transformation of proteins.

Curcumin-loaded food-grade nano-silica hybrid material exhibiting improved photodynamic effect and its application for the preservation of small yellow croaker (Larimichthys polyactis).

Two types of curcumin-loaded food-grade nano-silica (F-SiO2) hybrid materials were successfully synthesized using the rotary evaporation method (F-SiO2@Cur) and the adsorption method (Cur@F-SiO2). The microstructure and spectral analyses confirmed that the curcumin in F-SiO2@Cur was loaded within the nanopores in a non-aggregate form rather than being adsorbed onto the surface (Cur@F-SiO2). Additionally, F-SiO2@Cur exhibited remarkable water solubility (1510 ± 50.33 µg/mL) and photostability (a photodegradation ratio of only 59.22 %). Importantly, F-SiO2@Cur obtained a higher capacity for the generation of singlet oxygen (1O2) compared to control groups. Consequently, F-SiO2@Cur-mediated photodynamic inactivation (PDI) group attained the highest score in sensory evaluation and the best color protection effect in PDI experiment of small yellow croaker (Larimichthys polyactis) at 4 °C. Moreover, F-SiO2@Cur could effectively controlled total volatile basic nitrogen (TVB-N) content, pH, and total viable count (TVC), thereby prolonging the shelf life. Therefore, F-SiO2@Cur-mediated PDI is an effective fresh-keeping technology for aquatic products.

Preserving condensate structure and composition by lowering sequence complexity.

Biomolecular condensates play a vital role in organizing cellular chemistry. They selectively partition biomolecules, preventing unwanted cross-talk and buffering against chemical noise. Intrinsically disordered proteins (IDPs) serve as primary components of these condensates due to their flexibility and ability to engage in multivalent interactions, leading to spontaneous aggregation. Theoretical advancements are critical at connecting IDP sequences with condensate emergent properties to establish the so-called molecular grammar. We proposed an extension to the stickers and spacers model, incorporating heterogeneous, non-specific pairwise interactions between spacers alongside specific interactions among stickers. Our investigation revealed that while spacer interactions contribute to phase separation and co-condensation, their non-specific nature leads to disorganized condensates. Specific sticker-sticker interactions drive the formation of condensates with well-defined networked structures and molecular composition. We discussed how evolutionary pressures might emerge to affect these interactions, leading to the prevalence of low complexity domains in IDP sequences. These domains suppress spurious interactions and facilitate the formation of biologically meaningful condensates.

g-C3N4-based photocatalytic materials for converting CO2 into energy: a review.

Environmental pollution management and renewable energy development are humanity's biggest issues in the 21st century. The rise in atmospheric CO2, which has surpassed 400 parts per million, has stimulated research on CO2 reduction and conversion methods. Presently, photocatalytic conversion of CO2 to valuable hydrocarbons enables the transformation of solar energy into chemical energy and offers a novel avenue for energy conversion while regulating the greenhouse effect. This is an ideal strategy for simultaneously addressing environmental issues and the energy crisis. Photocatalysts are essential to photocatalytic processes. Photocatalyst is the core of photocatalytic technology, and graphite carbon nitride (g-C3N4) has attracted much attention because of its nonmetallic characteristics, and it has the characteristics of low cost, tunable electronic structure, easy manufacture and strong reducibility. However, its activity is not only affected by external reaction conditions, but also by the band gap structure, physical and chemical stability, surface morphology and specific surface area of the photocatalyst it. In this paper, the application progress of g-C3N4-based photocatalytic materials in CO2 reduction is reviewed, and the modification strategies of g-C3N4-based catalysts to obtain better catalytic efficiency and selectivity in CO2 photocatalytic reduction are summarized, and the future development of this material is prospected.

Elucidation of high-pressure processing toward microbial inhibition, physicochemical properties, collagen fiber and muscle structure of blood clam edible portion.

Impact of high-pressure processing (HP-P) on microbial inactivation, protein oxidation, collagen fiber, and muscle structure of the edible portion (EP) of blood clams (BC) was investigated. Aerobic plate count, Vibrio parahaemolyticus, V. vulnificus, other Vibrio spp. and Shewanella algae counts were not detectable when HP-P pressure of ≥300 MPa was applied. Carbonyl, disulphide bond content, and surface hydrophobicity upsurged as HP-P with augmenting pressure was employed. Protein with ∼53 kDa appeared when HP-P at 100 and 200 MPa was implemented. Increased pressure enhanced gap formation and abnormal muscle cell structure arrangements. HP-P also affected connective tissue, causing size reduction and disruption of the collagen filament fibers. However, firmness and toughness of BC-EP with HP-P ≤ 300 MPa were comparable to those of the control. HP-P at 300 MPa was therefore appropriate for treatment of BC with maintained textural properties, while less protein oxidation, collagen fiber and muscle structure disruption occurred.

Evaluation of left ventricular blood flow kinetic energy in patients with acute myocardial infarction by 4D Flow MRI: a preliminary study.

PURPOSE: To evaluate the intracavity left ventricular (LV) blood flow kinetic energy (KE) parameters using four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) in patients with acute myocardial infarction (AMI). METHODS: Thirty AMI patients and twenty controls were examined via CMR, which included cine imaging, late gadolinium enhancement (LGE) and global heart 4D flow imaging. The KE parameters were indexed to LV end-diastolic volume (EDV) to obtain average, systolic and diastolic KE as well as the proportion of LV in-plane KE (%). These parameters were compared between the AMI patients and controls and between the two subgroups. RESULTS: Analysis of the LV blood flow KE parameters at different levels of the LV cavity and in different segments of the same level showed that the basal level had the highest blood flow KE while the apical level had the lowest in the control group. There were no significant differences in diastolic KE, systolic in-plane KE and diastolic in-plane KE between the anterior wall and posterior wall (p > 0.05), only the systolic KE had a significant difference between them (p < 0.05). Compared with those in the control group, the average (10.7 ± 3.3 µJ/mL vs. 14.7 ± 3.6 µJ/mL, p < 0.001), systolic (14.6 ± 5.1 µJ/mL vs. 18.9 ± 3.9 µJ/mL, p = 0.003) and diastolic KE (7.9 ± 2.5 µJ/mL vs. 10.6 ± 3.8 µJ/mL, p = 0.018) were significantly lower in the AMI group. The average KE in the infarct segment was lower than that in the noninfarct segment in the AMI group (49.5 ± 18.7 µJ/mL vs. 126.3 ± 50.7 µJ/mL, p < 0.001), while the proportion of systolic in-plane KE increased significantly (61.8%±11.5 vs. 42.9%±14.4, p = 0.001). CONCLUSION: The 4D Flow MRI technique can be used to quantitatively evaluate LV regional hemodynamic parameters. There were differences in the KE parameters of LV blood flow at different levels and in different segments of the same level in healthy people. In AMI patients, the average KE of the infarct segment decreased, while the proportion of systolic in-plane KE significantly increased.

SIAH2 suppresses c-JUN pathway by promoting the polyubiquitination and degradation of HBx in hepatocellular carcinoma.

As an important protein encoded by hepatitis B virus (HBV), HBV X protein (HBx) plays an important role in the development of hepatocellular carcinoma (HCC). It has been shown that seven in absentia homologue 1 (SIAH1) could regulates the degradation of HBx through the ubiquitin-proteasome pathway. However, as a member of SIAH family, the regulatory effects of SIAH2 on HBx remain unclear. In this study, we first confirmed that SIAH2 could reduce the protein levels of HBx depending on its E3 ligase activity. Moreover, SIAH2 interacted with HBx and induced its K48-linked polyubiquitination and proteasomal degradation. Furthermore, we provided evidence that SIAH2 inhibits HBx-associated HCC cells proliferation by regulating HBx. In conclusion, our study identified a novel role for SIAH2 in promoting HBx degradation and SIAH2 exerts an inhibitory effect in the proliferation of HBx-associated HCC through inducing the degradation of HBx. Our study provides a new idea for the targeted degradation of HBx and may have great huge significance into providing novel evidence for the targeted therapy of HBV-infected HCC.

Celastrol reduces lung inflammation induced by multiwalled carbon nanotubes in mice via NF-κb-signaling pathway.

Multiwalled carbon nanotubes (MWCNTs) have numerous applications in the field of carbon nanomaterials. However, the associated toxicity concerns have increased significantly because of their widespread use. The inhalation of MWCNTs can lead to nanoparticle deposition in the lung tissue, causing inflammation and health risks. In this study, celastrol, a natural plant medicine with potent anti-inflammatory properties, effectively reduced the number of inflammatory cells, including white blood cells, neutrophils, and lymphocytes, and levels of inflammatory cytokines, such as IL-1ß, IL-6, and TNF-α, in mice lungs exposed to MWCNTs. Moreover, celastrol inhibited the activation of the NF-κB-signaling pathway. This study confirmed these findings by demonstrating comparable reductions in inflammation upon exposure to MWCNTs in mice with the deletion of NF-κB (P50-/-). These results indicate the utility of celastrol as a promising pharmacological agent for preventing MWCNT-induced lung tissue inflammation.

PRECEDE-PROCEED Model Nursing Intervention in Health Education for Parents of Obese Children.

Objective: To study the intervention effects of the health education and health promotion (PRECEDE-PROCEED) model on the health behaviors and quality of life of obese children and their parents. Methods: 524 patients who attended our pediatric obesity clinic from January to December 2021 were selected and divided into two groups: the control group (n = 262) and the test group (n = 262). The control group was guided by conventional weight reduction instruction, while the test group implemented the PRECEDE-PROCEED model. Based on this model, interventions were developed following the 9 links of the model, with tendency factors, contributing factors, and reinforcing factors as the core and 6 aspects of health behaviors were focused upon, and were followed up for 12 months. A home-made questionnaire scale was used to assess the subjects at their initial visit and one year after the intervention. Results: After the intervention, the awareness rate of obesity-related knowledge, support rate of attitude toward improving childhood obesity, awareness rate of disease harm caused by obesity, and formation rate of controlling childhood obesity behavior had significantly improved among the parents of the test group compared to the control group, with significant differences between the two groups (P < .05). Conclusion: The PRECEDE-PROCEED model can transform the way parents of obese children apply health education at home, improving health behaviors and quality of life.

Ultrasound-mediated delivery of doxorubicin to the brain results in immune modulation and improved responses to PD-1 blockade in gliomas.

Given the marginal penetration of most drugs across the blood-brain barrier, the efficacy of various agents remains limited for glioblastoma (GBM). Here we employ low-intensity pulsed ultrasound (LIPU) and intravenously administered microbubbles (MB) to open the blood-brain barrier and increase the concentration of liposomal doxorubicin and PD-1 blocking antibodies (aPD-1). We report results on a cohort of 4 GBM patients and preclinical models treated with this approach. LIPU/MB increases the concentration of doxorubicin by 2-fold and 3.9-fold in the human and murine brains two days after sonication, respectively. Similarly, LIPU/MB-mediated blood-brain barrier disruption leads to a 6-fold and a 2-fold increase in aPD-1 concentrations in murine brains and peritumoral brain regions from GBM patients treated with pembrolizumab, respectively. Doxorubicin and aPD-1 delivered with LIPU/MB upregulate major histocompatibility complex (MHC) class I and II in tumor cells. Increased brain concentrations of doxorubicin achieved by LIPU/MB elicit IFN-γ and MHC class I expression in microglia and macrophages. Doxorubicin and aPD-1 delivered with LIPU/MB results in the long-term survival of most glioma-bearing mice, which rely on myeloid cells and lymphocytes for their efficacy. Overall, this translational study supports the utility of LIPU/MB to potentiate the antitumoral activities of doxorubicin and aPD-1 for GBM.

Exosomes from umbilical cord mesenchymal stem cells ameliorate intervertebral disc degeneration via repairing mitochondrial dysfunction.

Background: Reactive oxygen species (ROS), predominantly generated by mitochondria, play a crucial role in the pathogenesis of intervertebral disc degeneration (IVDD). Reduction of ROS levels may be an effective strategy to delay IVDD. In this study, we assessed whether umbilical cord mesenchymal stem cell-exosomes (UCMSC-exos) can be used to treat IVDD by suppressing ROS production caused by mitochondrial dysfunction. Materials and methods: Human UCMSC-exos were isolated and identified. Nucleus pulposus cells (NPCs) were stimulated with H2O2 in the presence or absence of exosomes. Then, 4D label free quantitative (4D-LFQ) proteomics were used to analyze the differentially expressed (DE) proteins. Mitochondrial membrane potential (MMP), mitochondrial ROS and protein levels were determined via immunofluorescence staining, flow cytometry and western blotting respectively. Additionally, high-throughput sequencing was performed to identify the DE miRNAs in NPCs. Finally, therapeutic effects of UCMSC-exos were investigated in a puncture-induced IVDD rat model. Degenerative grades of rat IVDs were assessed using magnetic resonance imaging and histochemical staining. Results: UCMSC-exos effectively improved the viability of NPCs and restored the expression of the extracellular matrix (ECM) proteins, collagen type II alpha-1 (COL2A1) and matrix metalloproteinase-13 induced by H2O2. Additionally, UCMSC-exos not only reduced the total intracellular ROS and mitochondrial superoxide levels, but also increased MMP in pathological NPCs. 4D-LFQ proteomics and western blotting further revealed that UCMSC-exos up-regulated the levels of the mitochondrial protein, mitochondrial transcription factor A (TFAM), in H2O2-induced NPCs. High-throughput sequencing and qRT-PCR uncovered that UCMSC-exos down-regulated the levels of miR-194-5p, a potential negative regulator of TFAM, induced by H2O2. Finally, in vivo results showed that UCMSC-exos injection improved the histopathological structure and enhanced the expression levels of COL2A1 and TFAM in the rat IVDD model. Conclusions: Our findings suggest that UCMSC-exos promote ECM synthesis, relieve mitochondrial oxidative stress, and attenuate mitochondrial dysfunction in vitro and in vivo, thereby effectively treating IVDD. The translational potential of this article: This study provides solid experimental data support for the therapeutic effects of UCMSC-exos on IVDD, suggesting that UCMSC-exos will be a promising nanotherapy for IVDD.

Qingxiong Ointment and Its Active Ingredient, Shikonin Treat Psoriasis through HIF-1 Signaling Pathway.

BACKGROUND: Psoriasis is a common chronic inflammatory skin disorder. Qingxiong ointment (QX) is a natural medicinal combination frequently employed in clinical treatment of psoriasis. However, the active ingredients of QX and its precise mechanisms of improving psoriasis remain unclear. This study elucidated the effects of QX on an Imiquimod (IMQ)-induced mouse model of psoriasis while also exploring the regulation of the active ingredient of QX, shikonin, on the HIF-1 signaling pathway in HaCaT cells. METHODS: A mouse model of psoriasis was established through topical application of IMQ, and the local therapeutic effect of QX was evaluated using dorsal skin tissue with mouse psoriatic lesion and Psoriasis Area Severity Index (PASI) scores, hematoxylin-eosin (HE) staining, and immunohistochemical staining. Elisa and qPCR were employed to identify changes in the expression of inflammation-related factors in the mouse dorsal skin. Immunofluorescence was used to assess changes in the expression of T cell subsets before and after treatment with various doses of QX. HPLC was used to analyze the content of shikonin, and network pharmacology was employed to analyze the main targets of shikonin. Immunofluorescence was used to identify the effects of shikonin on the HIF-1 signaling pathway in IL6-induced psoriasis HaCaT cells. Finally, qPCR was used to identify the differential expression of the HIF-1 signaling pathway in skin tissues. RESULTS: QX significantly reduces PASI scores on the backs of IMQ-induced psoriasis mice. HE staining reveals alleviated epidermal thickness in the QX group. Immunohistochemical analysis shows a significant reduction in ICAM, KI67, and IL17 expression levels in the QX group. Immunofluorescence results indicate that QX can notably decrease the proportions of CD4+ T cells, γδ T cells, and CD8+ T cells while increasing the proportion of Treg cells. Network pharmacology analysis demonstrates that the main targets of shikonin are concentrated in the HIF-1 signaling pathway. Molecular docking results show favorable binding affinity between shikonin and key genes of the HIF-1 signaling pathway. Immunofluorescence results reveal that shikonin significantly reduces p-STAT3, SLC2A1, HIF1α, and NOS2 expression levels. qPCR results show significant downregulation of the HIF-1 signaling pathway at cellular and tissue levels. CONCLUSION: Our study revealed that QX can significantly reduce the dorsal inflammatory response in the IMQ-induced psoriasis mouse model. Furthermore, we discovered that its main component, shikonin, exerts its therapeutic effect by diminishing the HIF-1 signaling pathway in HaCaT cells.

SOFB is a comprehensive ensemble deep learning approach for elucidating and characterizing protein-nucleic-acid-binding residues.

Proteins and nucleic-acids are essential components of living organisms that interact in critical cellular processes. Accurate prediction of nucleic acid-binding residues in proteins can contribute to a better understanding of protein function. However, the discrepancy between protein sequence information and obtained structural and functional data renders most current computational models ineffective. Therefore, it is vital to design computational models based on protein sequence information to identify nucleic acid binding sites in proteins. Here, we implement an ensemble deep learning model-based nucleic-acid-binding residues on proteins identification method, called SOFB, which characterizes protein sequences by learning the semantics of biological dynamics contexts, and then develop an ensemble deep learning-based sequence network to learn feature representation and classification by explicitly modeling dynamic semantic information. Among them, the language learning model, which is constructed from natural language to biological language, captures the underlying relationships of protein sequences, and the ensemble deep learning-based sequence network consisting of different convolutional layers together with Bi-LSTM refines various features for optimal performance. Meanwhile, to address the imbalanced issue, we adopt ensemble learning to train multiple models and then incorporate them. Our experimental results on several DNA/RNA nucleic-acid-binding residue datasets demonstrate that our proposed model outperforms other state-of-the-art methods. In addition, we conduct an interpretability analysis of the identified nucleic acid binding residue sequences based on the attention weights of the language learning model, revealing novel insights into the dynamic semantic information that supports the identified nucleic acid binding residues. SOFB is available at https://github.com/Encryptional/SOFB and https://figshare.com/articles/online_resource/SOFB_figshare_rar/25499452 .

Bridging Nickel-MOF and Copper Single Atoms/Clusters with H-Substituted Graphdiyne for the Tandem Catalysis of Nitrate to Ammonia.

Interfacial engineering of synergistic catalysts is one of the keys to achieving multiple proton-coupled electron transfer processes in nitrate-to-ammonia conversion. Herein, by joining ultrathin nickel-based metal-organic framework (denoted Ni-MOF) nanosheets with few-layered hydrogen-substituted graphdiyne-supported copper single atoms and clusters (denoted HsGDY@Cu), a tandem catalyst of Ni-MOFs@HsGDY@Cu with dual-active interfaces was developed for the concerted catalysis of nitrate-to-ammonia. In such a system, the sandwiched HsGDY layer could serve as a bridge to connect the coordinated unsaturated Ni2+ sites with Cu single atoms/clusters in a limited range of 0 to 3.6 nm. From Ni2+ to Cu, via the hydrogen spillover process, the hydrogen radicals (H·) generated at the unsaturated Ni2+ sites could migrate across HsGDY to the Cu sites to participate in the transformation of *HNO3 to NH3. From Cu to Ni2+, bypassing the higher reaction energy for *HNO3 formation on the Ni2+ sites, the NO2- detached from the Cu sites could diffuse onto the unsaturated Ni2+ sites to form NH3 as well. The combined results make this hybrid a tandem catalyst with dual active sites for the catalysis of nitrate-to-ammonia conversion with improved Faradaic efficiency at lower overpotentials.

Insights from the 2nd China intelligent sleep staging competition.

STUDY OBJECTIVES: Artificial intelligence (AI) is quickly advancing in the field of sleep medicine, which bodes well for the potential of actual clinical use. In this study, an analysis of the 2nd China Intelligent Sleep Staging Competition was conducted to gain insights into the general level and constraints of AI-assisted sleep staging in China. METHODS: The outcomes of 10 teams from the children's track and 13 teams from the adult track were investigated in this study. The analysis included overall performance, differences between five different sleep stages, variations across subjects, and performance during stage transitions. RESULTS: The adult track's accuracy peaked at 80.46%, while the children's track's accuracy peaked at 88.96%. On average, accuracy rates stood at 71.43% for children and 68.40% for adults. All results were produced within a mere 5-min timeframe. The N1 stage was prone to misclassification as W, N2, and R stages. In the adult track, significant differences were apparent among subjects (p < 0.05), whereas in the children's track, such differences were not observed. Nonetheless, both tracks experienced a performance decline during stage transitions. CONCLUSIONS: The computational speed of AI is remarkably fast, simultaneously holding the potential to surpass the accuracy of physicians. Improving the machine learning model's classification of the N1 stage and transitional periods between stages, along with bolstering its robustness to individual subject variations, is imperative for maximizing its ability in assisting clinical scoring.

High yield electrosynthesis of oxygenates from CO using a relay Cu-Ag co-catalyst system.

As a sustainable alternative to fossil fuel-based manufacture of bulk oxygenates, electrochemical synthesis using CO and H2O as raw materials at ambient conditions offers immense appeal. However, the upscaling of the electrosynthesis of oxygenates encounters kinetic bottlenecks arising from the competing hydrogen evolution reaction with the selective production of ethylene. Herein, a catalytic relay system that can perform in tandem CO capture, activation, intermediate transfer and enrichment on a Cu-Ag composite catalyst is used for attaining high yield CO-to-oxygenates electrosynthesis at high current densities. The composite catalyst Cu/30Ag (molar ratio of Cu to Ag is 7:3) enables high efficiency CO-to-oxygenates conversion, attaining a maximum partial current density for oxygenates of 800 mA cm-2 at an applied current density of 1200 mA cm-2, and with 67 % selectivity. The ability to finely control the production of ethylene and oxygenates highlights the principle of efficient catalyst design based on the relay mechanism.

A Competing Risk Nomogram for Prediction of Prognosis in Patients With Primary Squamous Cell Thyroid Carcinoma.

Objective: Primary squamous cell thyroid carcinoma (PSCTC) is an extremely rare carcinoma, accounting for less than 1% of all thyroid carcinomas. However, the factors contributing to PSCTC outcomes remain unclear. This study aimed to identify the prognostic factors and develop a prognostic predictive model for patients with PSCTC. Methods: The analysis included patients diagnosed with thyroid carcinoma between 1975 and 2016 from the Surveillance, Epidemiology, and End Results database. Prognostic differences among the 5 pathological types of thyroid carcinomas were analyzed. To determine prognostic factors in PSCTC patients, the Cox regression model and Fine-Gray competing risk model were utilized. Based on the Fine-Gray competing risk model, a nomogram was established for predicting the prognosis of patients with PSCTC. Results: A total of 198,757 thyroid carcinoma patients, including 218 PSCTC patients, were identified. We found that PSCTC and anaplastic thyroid cancer had the worst prognosis among the 5 pathological types of thyroid carcinoma (P < .001). According to univariate and multivariate Cox regression analyses, age (71-95 years) was an independent risk factor for poorer overall survival and disease-specific survival in PSCTC patients. Using Fine-Gray regression analysis, the total number of in situ/malignant tumors for patient (Number 1) (≥2) was identified as an independent protective factor for prognosis of PSCTC. The area under the curve, the concordance index (C-index), calibration curves and decision curve analysis revealed that the nomogram was capable of predicting the prognosis of PSCTC patients accurately. Conclusion: The competing risk nomogram is highly accurate in predicting prognosis for patients with PSCTC, which may help clinicians to optimize individualized treatment decisions.

Short-term exposure to antibiotics begets long-term disturbance in gut microbial metabolism and molecular ecological networks.

BACKGROUND: Antibiotic exposure can occur in medical settings and from environmental sources. Long-term effects of brief antibiotic exposure in early life are largely unknown. RESULTS: Post a short-term treatment by ceftriaxone to C57BL/6 mice in early life, a 14-month observation was performed using 16S rRNA gene-sequencing technique, metabolomics analysis, and metagenomics analysis on the effects of ceftriaxone exposure. Firstly, the results showed that antibiotic pre-treatment significantly disturbed gut microbial α and ß diversities (P < 0.05). Both Chao1 indices and Shannon indices manifested recovery trends over time, but they didn't entirely recover to the baseline of control throughout the experiment. Secondly, antibiotic pre-treatment reduced the complexity of gut molecular ecological networks (MENs). Various network parameters were affected and manifested recovery trends over time with different degrees, such as nodes (P < 0.001, R2 = 0.6563), links (P < 0.01, R2 = 0.4543), number of modules (P = 0.0672, R2 = 0.2523), relative modularity (P = 0.6714, R2 = 0.0155), number of keystones (P = 0.1003, R2 = 0.2090), robustness_random (P = 0.79, R2 = 0.0063), and vulnerability (P = 0.0528, R2 = 0.28). The network parameters didn't entirely recover. Antibiotic exposure obviously reduced the number of key species in gut MENs. Interestingly, new keystones appeared during the recovery process of network complexity. Changes in network stability might be caused by variations in network complexity, which supports the ecological theory that complexity begets stability. Besides, the metabolism profiles of the antibiotic group and control were significantly different. Correlation analysis showed that antibiotic-induced differences in gut microbial metabolism were related to MEN changes. Antibiotic exposure also caused long-term effects on gut microbial functional networks in mice. CONCLUSIONS: These results suggest that short-term antibiotic exposure in early life will cause long-term negative impacts on gut microbial diversity, MENs, and microbial metabolism. Therefore, great concern should be raised about children's brief exposure to antibiotics if the results observed in mice are applicable to humans. Video Abstract.