Dose-response association between walking speed and all-cause mortality: A systematic review and meta-analysis of cohort studies.

This review aims to investigate the dose-response relationship between walking speed and all-cause mortality. PubMed, Web of Science, Embase and Cochrane Library were searched to September, 2023 for cohort studies. A meta-analysis estimated the overall hazard ratio (HR) of mortality incidence and 95% Confidence Interval (CI) for individuals with the fastest walking speed compared to those with the slowest walking speed. Subgroup analyses were conducted based on sex, age and speed-measuring methods. Dose-response meta-analyses were examined by using "mvmeta" packages available in STATA. A total of 13 studies involving 530,841 participants were included. Of these, 11 studies provided data for dose-response meta-analyses. Individuals in the fastest walking-speed category had a 43% lower risk of all-cause mortality compared to those in the slowest walking-speed category (HR = 0.57, 95% CI 0.48-0.66). There was an inverse linear dose-response relationship between walking speed and all-cause mortality; for every 0.1 m/s increment in walking speed, the risk of mortality decreased by 6% (HR = 0.94; 0.92-0.96). There was an inverse nonlinear dose-response relationship between them when participants' age was larger than 65 years, but linear dose-response relationships were detected in both the timed walking speed test and self-reported walking speed measurements.

moPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models.

The ability to precisely target specific motifs on disease-related proteins, whether conserved epitopes on viral proteins, intrinsically disordered regions within transcription factors, or breakpoint junctions in fusion oncoproteins, is essential for modulating their function while minimizing off-target effects. Current methods struggle to achieve this specificity without reliable structural information. In this work, we introduce a mo tif-specific PPI t argeting algorithm, moPPIt , for de novo generation of motif-specific peptide binders from the target protein sequence alone. At the core of moPPIt is BindEvaluator, a transformer-based model that interpolates protein language model embeddings of two proteins via a series of multi-headed self-attention blocks, with a key focus on local motif features. Trained on over 510,000 annotated PPIs, BindEvaluator accurately predicts target binding sites given protein-protein sequence pairs with a test AUC > 0.94, improving to AUC > 0.96 when fine-tuned on peptide-protein pairs. By combining BindEvaluator with our PepMLM peptide generator and genetic algorithm-based optimization, moPPIt generates peptides that bind specifically to user-defined residues on target proteins. We demonstrate moPPIt's efficacy in computationally designing binders to specific motifs, first on targets with known binding peptides and then extending to structured and disordered targets with no known binders. In total, moPPIt serves as a powerful tool for developing highly specific peptide therapeutics without relying on target structure or structure-dependent latent spaces.

Exosomes-mediated retinoic acid disruption: A link between gut microbiota depletion and impaired spermatogenesis.

Gut microbiota symbiosis faces enormous challenge with increasing exposure to drugs such as environmental poisons and antibiotics. The gut microbiota is an important component of the host microbiota and has been proven to be involved in regulating spermatogenesis, but the molecular mechanism is still unclear. A male mouse model with gut microbiota depletion/dysbiosis was constructed by adding combined antibiotics to free drinking water, and reproductive parameters such as epididymal sperm count, testicular weight and paraffin sections were measured. Testicular transcriptomic and serum metabolomic analyses were performed to reveal the molecular mechanism of reproductive dysfunction induced by gut microbiota dysbiosis in male mice.This study confirms that antibiotic induced depletion of gut microbiota reduces sperm count in the epididymis and reduces germ cells in the seminiferous tubules in male mice. Further study showed that exosomes isolated from microbiota-depleted mice led to abnormally high levels of retinoic acid and decrease in the number of germ cells in the seminiferous tubules and sperm in the epididymis. Finally, abnormally high levels of retinoic acid was confirmed to disrupted meiotic processes, resulting in spermatogenesis disorders. This study proposed the concept of the gut microbiota-exosome-retinoic acid-testicular axis and demonstrated that depletion of the gut microbiota caused changes in the function of exosomes, which led to abnormal retinoic acid metabolism in the testis, thereby impairing meiosis and spermatogenesis processes.

Tunable Ag Nanocavity Enhanced Green Electroluminescence from SiNx:O Light-Emitting Diode.

As the driving source, highly efficient silicon-based light emission is urgently needed for the realization of optoelectronic integrated chips. Here, we report that enhanced green electroluminescence (EL) can be obtained from oxygen-doped silicon nitride (SiNx:O) films based on an ordered and tunable Ag nanocavity array with a high density by nanosphere lithography and laser irradiation. Compared with that of a pure SiNxO device, the green electroluminescence (EL) from the SiNx:O/Ag nanocavity array device can be increased by 7.1-fold. Moreover, the external quantum efficiency of the green electroluminescence (EL) is enhanced 3-fold for SiNx:O/Ag nanocavity arrays with diameters of 300 nm. The analysis of absorption spectra and the FDTD calculation reveal that the localized surface plasmon (LSP) resonance of size-controllable Ag nanocavity arrays and SiNx:O films play a key role in the strong green EL. Our discovery demonstrates that SiNx:O films coupled with tunable Ag nanocavity arrays are promising for silicon-based light-emitting diode devices of the AI period in the future.

Diagnostic agreement between visual examination and an automated scanner system with fluorescence for detecting and classifying occlusal carious lesions in primary teeth.

OBJECTIVES: To investigate the in vivo diagnostic agreement between visual examination (VE) using the International Caries Detection and Assessment System (ICDAS) and an automated scanner system for detecting and classifying carious lesions in primary teeth. METHODS: 5-year-old children (n = 216) underwent VE and intraoral scanning (TRIOS 4, 3Shape TRIOS A/S, Copenhagen, Denmark). Dental caries experience was recorded for each tooth surface using ICDAS. An automated, fluorescence-based caries scoring system was applied to eligible primary teeth occlusal surfaces on the 3D models using commercially available software. The automated system classified surfaces as sound, initial caries (ICDAS 01/02), or moderate-extensive caries (ICDAS ≥03). The diagnostic agreement was investigated using multi-level modelling and intraclass correlation coefficients. Analyses were repeated at both the initial threshold (ICDAS ≥01) and the moderate-extensive threshold (ICDAS ≥03). RESULTS: 213 participants were included in the study, and 1525 primary molar occlusal surfaces were included in the analysis. The odds of detecting caries using the automated system were 46 % lower at the initial disease threshold (OR 0.54, 95 % CI 0.39-0.74) and 70 % lower at the moderate-extensive disease threshold (OR 0.30, 95 % CI 0.16-0.58) compared to VE. The intraclass correlation estimates at the initial and moderate-extensive thresholds were 0.90 (95 % CI 0.70-0.96) and 0.76 (95 % CI 0.22-0.94) respectively. CONCLUSION: The automated system is less likely to detect initial lesions and is more likely to underestimate lesion severity relative to visual examination using ICDAS. CLINICAL SIGNIFICANCE: Clinically, using the automated tool to replace thorough visual inspection in primary teeth could result in missed opportunities to provide professional or self-care to arrest or reverse early disease. Additionally, it could misclassify moderate lesions as initial caries, potentially leading to complications associated with the delayed management of dental caries.

Causal associations between both psoriasis and psoriatic arthritis and multiple autoimmune diseases: a bidirectional two-sample Mendelian randomization study.

Background: Numerous observational studies have identified associations between both psoriasis (PsO) and psoriatic arthritis (PsA), and autoimmune diseases (AIDs); however, the causality of these associations remains undetermined. Methods: We conducted a bidirectional two-sample Mendelian Randomization study to identify causal associations and directions between both PsO and PsA and AIDs, such as systemic lupus erythematosus (SLE), Crohn's disease (CD), ulcerative colitis (UC), multiple sclerosis (MS), uveitis, bullous pemphigoid (BP), Hashimoto's thyroiditis (HT), rheumatoid arthritis (RA), vitiligo, and ankylosing spondylitis (AS). The causal inferences were drawn by integrating results from four regression models: Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, and Maximum Likelihood. Furthermore, we performed sensitivity analyses to confirm the reliability of our findings. Results: The results showed that CD [IVW odds ratio (ORIVW), 1.11; 95% confidence interval (CI), 1.06-1.17; P = 8.40E-06], vitiligo (ORIVW, 1.16; 95% CI, 1.05-1.28; P = 2.45E-03) were risk factors for PsO, while BP may reduce the incidence of PsO (ORIVW, 0.91; 95% CI, 0.87-0.96; P = 1.26E-04). CD (ORIVW, 1.07; 95% CI, 1.02-1.12; P = 0.01), HT (ORIVW, 1.23; 95% CI, 1.08-1.40; P = 1.43E-03), RA (ORIVW, 1.11; 95% CI, 1.02-1.21, P = 2.05E-02), AS (ORIVW, 2.18; 95% CI, 1.46-3.27; P = 1.55E-04), SLE (ORIVW, 1.04; 95% CI, 1.01-1.08; P = 1.07E-02) and vitiligo (ORIVW, 1.27; 95% CI, 1.14-1.42; P = 2.67E-05) were risk factors for PsA. Sensitivity analyses had validated the reliability of the results. Conclusions: Our study provides evidence for potential causal relationships between certain AIDs and both PsO and PsA. Specifically, CD and vitiligo may increase the risk of developing PsO, while CD, HT, SLE, RA, AS, and vitiligo may elevate the risk for PsA. Additionally, it is crucial to closely monitor the condition of PsO patients with specific AIDs, as they have a higher likelihood of developing PsA than those without AIDs. Moving forward, greater attention should be paid to PsA and further exploration of other PsO subtypes is warranted.

CircCFL1 Promotes TNBC Stemness and Immunoescape via Deacetylation-Mediated c-Myc Deubiquitylation to Facilitate Mutant TP53 Transcription.

Triple-negative breast cancer (TNBC) is the most malignant subtype of breast cancer. TP53, which has a mutation rate of ≈70%-80% in TNBC patients, plays oncogenic roles when mutated. However, whether circRNAs can exert their effects on TNBC through regulating mutant TP53 has not been well evaluated. In this study, circCFL1, which is highly expressed in TNBC cells and tissues and has prognostic potential is identified. Functionally, circCFL1 promoted the proliferation, metastasis and stemness of TNBC cells. Mechanistically, circCFL1 acted as a scaffold to enhance the interaction between HDAC1 and c-Myc, further promoting the stability of c-Myc via deacetylation-mediated inhibition of K48-linked ubiquitylation. Stably expressed c-Myc further enhanced the expression of mutp53 in TNBC cells with TP53 mutations by directly binding to the promoter of TP53, which promoted the stemness of TNBC cells via activation of the p-AKT/WIP/YAP/TAZ pathway. Moreover, circCFL1 can facilitate the immune escape of TNBC cells by promoting the expression of PD-L1 and suppressing the antitumor immunity of CD8+ T cells. In conclusion, the results revealed that circCFL1 plays an oncogenic role by promoting the HDAC1/c-Myc/mutp53 axis, which can serve as a potential diagnostic biomarker and therapeutic target for TNBC patients with TP53 mutations.

Nanoemulsion based lipid nanoparticles for effective demethylcantharidin delivery to cure liver cancer.

Demethylcantharidin (DEM) is a widely used antitumor drug; however, its poor tumor targeting and serious organotoxicity limit its application. The aim of this study was to develop a new drug delivery system for efficient delivery of DEM. Nanoemulsion based lipid nanoparticles containing demethylcantharidin (DNLNs) were prepared by loading nanoemulsions into lipid nanoparticles. The cells proliferation, apoptosis, cycle, and uptake were investigated by Cell counting kit-8 (CCK-8), flow cytometry, and in situ fluorescence assays, respectively. Then, we established the H22 tumor-bearing mouse model to evaluate the antitumor efficacy of DNLNs and further studied its organ toxicity and distribution. DNLNs significantly inhibited the proliferation and promoted apoptosis of H22 cells, and H22 cells could take up more DNLNs. Compared with DEM, DNLNs had certain tumor-targeting properties, and the tumor inhibition rate increased by 23.24%. Moreover, DNLNs can increase white blood cell count and reduce organ toxicity. This study paves the way for nanoemulsion-based lipid nanoparticle (NLNs)-efficient DEM delivery to treat liver cancer.

Novel Jatrophane Diterpenoids from Euphorbia esula Promotes Lipid Clearance by Transcriptional Regulation of PCSK9.

PCSK9 has been recognized as an efficient target for hyperlipidemia and related cardiovascular/cerebrovascular diseases. However, PCSK9 inhibitors in the clinic are all biological products, and no small molecules are available yet. In the current work, we discovered that the crude extract of Euphorbia esula (E. esula) promoted LDL uptake in vitro and then obtained 8 new and 12 known jatrophane diterpenoids by activity-guided isolation. After summarized their structure-activity relationship of PCSK9 inhibition, we selected compound 11 (C11) with potent activity and high abundance to investigate its mechanism and in vivo efficacy. Mechanistically, C11 bound with HNF1α to influence its nuclear distribution and subsequently inhibit PCSK9 transcription, thereby enhancing LDLR and promoting LDL uptake. Moreover, C11 demonstrated obvious lipid-lowering activity in HFD mouse model. In conclusion, we first revealed the novel application of E. esula in the discovery of a lipid-lowering candidate and highlighted the potential of C11 in the treatment of hyperlipidemia.

Autocrine and paracrine effects of MDK promote lymph node metastasis of cervical squamous cell carcinoma.

Lymph node metastasis (LNM) is the main metastatic pathway of cervical cancer, which is closely related to 5-year survival rate of cervical squamous cell carcinoma (CSCC), yet the underlying mechanism remains unconfirmed. In this study, we show that midkine (MDK) was highly expressed in CSCC and overexpression of MDK was associated with CSCC LNM. Functional investigations demonstrated that MDK promoted LNM by enhancing proliferation, migration and invasion capacity of cervical cancer cells, facilitating lymphangiogenesis and down-regulating the expression of tight junction proteins of human lymphatic endothelial cells (HLECs). MDK exerted these biological effects by interacting with Syndecan-1 and activating PI3K/AKT and p38 MAPK pathways. A retrospective study showed that s-MDK was related to LNM. s-MDK combined with serum-squamous cell carcinoma antigen(s-SCCA) improved the diagnostic accuracy of CSCC LNM. These findings established a new mechanism of LNM and highlighted MDK as a candidate tumor biomarker and therapeutic target in CSCC.

Trim21-mediated CCT2 ubiquitination suppresses malignant progression and promotes CD4+T cell activation in breast cancer.

Breast cancer remains a significant global health challenge, and its mechanisms of progression and metastasis are still not fully understood. In this study, analysis of TCGA and GEO datasets revealed a significant increase in CCT2 expression in breast cancer tissues, which was associated with poor prognosis in breast cancer patients. Functional analysis revealed that CCT2 promoted breast cancer growth and metastasis through activation of the JAK2/STAT3 signaling pathway. Additionally, the E3 ubiquitin ligase Trim21 facilitated CCT2 ubiquitination and degradation, significantly reversing the protumor effects of CCT2. Most interestingly, we discovered that exosomal CCT2 derived from breast cancer cells suppressed the activation and proinflammatory cytokine secretion of CD4+ T cell. Mechanistically, exosomal CCT2 constrained Ca2+-NFAT1 signaling, thereby reducing CD40L expression on CD4+ T cell. These findings highlight CCT2 upregulation as a potential driver of breast cancer progression and immune evasion. Our study provides new insights into the molecular mechanisms underlying breast cancer progression, suggesting that CCT2 is a promising therapeutic target and prognostic predictor for breast cancer.

Modifiable risk factors for hepatocellular carcinoma in patients with metabolic dysfunction-associated steatotic liver disease: a meta-analysis.

BACKGROUND AND AIMS: The increasing incidence of metabolic dysfunction-associated steatotic liver disease (MASLD) has led to a gradual increase in MASLD-related hepatocellular carcinomas (HCC). In this context, we aimed to investigate the association between modifiable factors and the risk of incident HCC in patients with MASLD. METHODS: Two authors independently searched electronic databases (PubMed, Embase, and the Cochrane Library) from their inception to April 1 2023. Observational studies reporting an association between modifiable risk factors and MASLD-related HCC were eligible for inclusion. The effect size on the study outcomes was calculated using a random-effects model and was presented as a risk ratio with 95% confidence interval. RESULTS: A total of 31 studies covering 1.02 million individuals were included. Regarding lifestyle factors, smoking and alcohol consumption were associated with 30% [1.30 (1.08-1.57)] and 140% [2.41 (1.03-5.65)] risk increase of MASLD-related HCC . Regarding metabolic risk factors, patients with MASLD who were overweight or obese [1.31 (1.13-1.52)], had diabetes [2.08 (1.71-2.53)] and hypertension[1.42 (1.12-1.80)] had a higher risk of developing HCC, while dyslipidemia was negatively associated with MASLD-HCC [0.78 (0.65-0.93)]. The use of metformin, statin and aspirin was associated with 18% [0.82 (0.68-0.98)], 55% [0.45 (0.36-0.56)] and 36% [0.64 (0.44-0.92)] risk reduction in incident HCC, respectively. CONCLUSIONS: This comprehensive systematic review and meta-analysis showed statistically significant increases in the risk of incident HCC inpatients with MASLD due to smoking, alcohol use, obesity, diabetes and hypertension, whereas metformin, statin and aspirin therapy might modify disease progression.

Radiomics as a tool for prognostic prediction in transarterial chemoembolization for hepatocellular carcinoma: a systematic review and meta-analysis.

INTRODUCTION: Transarterial chemoembolization (TACE) is one of the predominant locoregional therapeutic modalities for addressing hepatocellular carcinoma (HCC). However, achieving precise prognostic predictions and effective patient selection remains a challenging pursuit. The primary objective of this systematic review and meta-analysis is to evaluate the efficacy of radiomics in forecasting the prognosis associated with TACE treatment. METHODS: A comprehensive exploration of pertinent original studies was undertaken, encompassing databases of PubMed, Web of Science and Embase. The studies' quality was meticulously evaluated employing the quality assessment of diagnostic accuracy studies 2 (QUADAS-2), the radiomics quality score (RQS) and the METhodological RadiomICs Score (METRICS). Pooled statistics, along with 95% confidence intervals (95% CI), were computed for sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR). Additionally, a summary receiver operating characteristic curve (sROC) was generated. To discern potential sources of heterogeneity, meta-regression and subgroup analyses were performed. RESULTS: The systematic review incorporated 29 studies, comprising a total of 5483 patients, with 14 studies involving 2691 patients qualifying for inclusion in the meta-analysis. The assessed studies exhibited commendable quality with regard to bias risk, with mean RQS of 12.90 ± 5.13 (35.82% ± 14.25%) and mean METRICS of 62.98% ± 14.58%. The pooled sensitivity was 0.83 (95% CI: 0.78-0.87), specificity was 0.86 (95% CI: 0.79-0.92), PLR was 6.13 (95% CI: 3.79-9.90), and NLR was 0.20 (95% CI: 0.15-0.27). The area under the sROC was 0.90 (95% CI: 0.87-0.93). Significant heterogeneity within all the included studies was observed, while meta-regression and subgroup analyses revealed homogeneous and promising findings in subgroups where principal methodological variables such as modeling algorithms, imaging modalities, and imaging phases were specified. CONCLUSION: Radiomics models have exhibited robust predictive capabilities concerning prognosis subsequent to TACE, thereby presenting promising prospects for clinical translation.

Development and Validation of a Biparametric MRI Deep Learning Radiomics Model with Clinical Characteristics for Predicting Perineural Invasion in Patients with Prostate Cancer.

RATIONALE AND OBJECTIVES: Perineural invasion (PNI) is an important prognostic biomarker for prostate cancer (PCa). This study aimed to develop and validate a predictive model integrating biparametric MRI-based deep learning radiomics and clinical characteristics for the non-invasive prediction of PNI in patients with PCa. MATERIALS AND METHODS: In this prospective study, 557 PCa patients who underwent preoperative MRI and radical prostatectomy were recruited and randomly divided into the training and the validation cohorts at a ratio of 7:3. Clinical model for predicting PNI was constructed by univariate and multivariate regression analyses on various clinical indicators, followed by logistic regression. Radiomics and deep learning methods were used to develop different MRI-based radiomics and deep learning models. Subsequently, the clinical, radiomics, and deep learning signatures were combined to develop the integrated deep learning-radiomics-clinical model (DLRC). The performance of the models was assessed by plotting the receiver operating characteristic (ROC) curves and precision-recall (PR) curves, as well as calculating the area under the ROC and PR curves (ROC-AUC and PR-AUC). The calibration curve and decision curve were used to evaluate the model's goodness of fit and clinical benefit. RESULTS: The DLRC model demonstrated the highest performance in both the training and the validation cohorts, with ROC-AUCs of 0.914 and 0.848, respectively, and PR-AUCs of 0.948 and 0.926, respectively. The DLRC model showed good calibration and clinical benefit in both cohorts. CONCLUSION: The DLRC model, which integrated clinical, radiomics, and deep learning signatures, can serve as a robust tool for predicting PNI in patients with PCa, thus aiding in developing effective treatment strategies.

Biparametric MRI of the prostate radiomics model for prediction of pelvic lymph node metastasis in prostate cancers : a two-centre study.

OBJECTIVES: Exploring the value of adding correlation analysis (radiomic features (RFs) of pelvic metastatic lymph nodes and primary lesions) to screen RFs of primary lesions in the feature selection process of establishing prediction model. METHODS: A total of 394 prostate cancer (PCa) patients (263 in the training group, 74 in the internal validation group and 57 in the external validation group) from two tertiary hospitals were included in the study. The cases with pelvic lymph node metastasis (PLNM) positive in the training group were diagnosed by biopsy or MRI with a short-axis diameter ≥ 1.5 cm, PLNM-negative cases in the training group and all cases in validation group were underwent both radical prostatectomy (RP) and extended pelvic lymph node dissection (ePLND). The RFs of PLNM-negative lesion and PLNM-positive tissues including primary lesions and their metastatic lymph nodes (MLNs) in the training group were extracted from T2WI and apparent diffusion coefficient (ADC) map to build the following two models by fivefold cross-validation: the lesion model, established according to the primary lesion RFs selected by t tests and absolute shrinkage and selection operator (LASSO); the lesion-correlation model, established according to the primary lesion RFs selected by Pearson correlation analysis (RFs of primary lesions and their MLNs, correlation coefficient > 0.9), t test and LASSO. Finally, we compared the performance of these two models in predicting PLNM. RESULTS: The AUC and the DeLong test of AUC in the lesion model and lesion-correlation model were as follows: training groups (0.8053, 0.8466, p = 0.0002), internal validation group (0.7321, 0.8268, p = 0.0429), and external validation group (0.6445, 0.7874, p = 0.0431), respectively. CONCLUSION: The lesion-correlation model established by features of primary tumors correlated with MLNs has more advantages than the lesion model in predicting PLNM.

Application of S-transform-based nonlinear processing for accurate LIBS quantitative analysis of iron ore slurry.

Real-time Fe content monitoring in iron ore slurry is crucial for evaluating concentrate quality and enhancing mineral processing efficiency. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for the online monitoring of elemental content at industrial sites. However, LIBS measurements are hampered by the matrix effect and the self-absorption effect, limiting the precision of linear analytical processes. To overcome this, we propose to introduce a nonlinear processing unit based on the S-transform to incorporate nonlinearity into the data analysis process. This approach integrates a feature selection unit based on the spectral distance variable selection method (SDVS), a nonlinear processing unit based on the S-transform (ST), and a partial least squares regression model (PLS). To demonstrate the improvement in accuracy achieved through nonlinear processing, a comparative analysis involving five models, Raw-PLS, SDVS-PLS, ST-PLS, SDVS-ANN, and SDVS-ST-PLS, is conducted. The results reveal a significant improvement in the performance of the SDVS-ST-PLS model, effectively facilitating the successful application of the LIBSlurry analyzer to the mineral flotation process.

Sesquiterpene lactones from Tithonia diversifolia with ferroptosis-inducing activities.

Eight previously undescribed sesquiterpene lactones (1-8), together with six known ones (9-14) were isolated from the aerial parts of Tithonia diversifolia (Hemsl.) A. Gray. The absolute configurations of these compounds were elucidated using HRMS, NMR spectroscopy, optical rotation measurements, X-ray crystallography, and ECD. Among them, sesquiterpene lactones 2-4 share a unique carbon skeleton with a rare C-3/C-4 ring-opened structure. Compounds 1 and 8 showed moderate inhibitory effects toward CT26 murine colon carcinoma cells by promoting lipid ROS production, highlighting their potential as ferroptosis inducers.

Infrared photodetectors based on wide bandgap two-dimensional transition metal dichalcogenides via efficient two-photon absorption.

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have attracted considerable attention due to their outstanding optoelectronic properties and ease of integration, making them ideal candidates for high-performance photodetectors. However, the excessive width of the bandgap in some 2D TMDs presents a challenge for achieving infrared photodetection. One approach to broaden the photoresponse wavelength range of TMDs is through the utilization of two-photon absorption (TPA) process. Unfortunately, the inefficiency of TPA hinders its application in infrared photodetection. In this study, we propose the design of two photodetectors utilizing high TPA coefficient materials, specifically ReSe2and MoS2, to exploit their TPA capability and extend the photoresponse to the near-infrared region at 1550 nm. The ReSe2photodetector demonstrates an unprecedented responsivity of 43µA W-1, surpassing that of current single-material TPA photodetectors. Similarly, the MoS2photodetector achieves a responsivity of 18µA W-1, comparable to state-of-the-art TPA photodetectors. This research establishes the potential of high TPA coefficient 2D TMDs for infrared photodetection.

The association of gender with functional outcome in thrombolysed stroke: A secondary analysis of INTRECIS study.

Background and Purpose: Sex differences in acute ischemic stroke have been widely investigated, but the difference in acute ischemic stroke patients who received intravenous thrombolysis is not well understood. The current study was to investigate the issue based on a prospective cohort. Methods: From the Intravenous Thrombolysis Registry for Chinese Ischemic Stroke within 4.5h onset (INTRECIS) cohort, a total of 953 eligible patients with acute ischemic stroke were enrolled in final analysis. Based on 3-month modified Rankin scale score (mRS), patients were classified into good outcome group (mRS 0-1) and poor outcome group (mRS 2-6). Univariate and multivariate logistic regression analyses were used to identify predictive factors for clinical outcome in male or female patients. Results: Of the 953 patients treated with intravenous thrombolysis, 314 (32.9 %) were women. At day 90, we found no significant gender differences in good outcome (72.5 % vs 65.6 %, adjusted p = 0.414). We got the same results after propensity score matching (69.5 % vs 63.4 %, adjusted p = 0.637). Furthermore, we found that initial National Institute of Health Stroke Scale (NIHSS) score (odd ratio [OR] 0.877; 95 % CI 0.847-0.909, p < 0.001) and serum creatinine (OR 0.993; 95 % CI 0.986-1.000, p = 0 0.043) were found to be independent risk factors for poor outcome in male patients, while initial NIHSS score (OR 0.879; 95 % CI 0.839-0.920, p < 0.001), age (OR 0.970; 95 % CI 0.946-0.995, p = 0.017), systolic blood pressure (OR 0.984; 95 % CI 0.972-0.996, p = 0.007) and small artery occlusion (OR 2.718; 95 % CI 1.065-6.936, p = 0.036) in female patients. Conclusions: In this study, we found no gender difference in clinical outcome of thrombolysed stroke patients, but a difference in risk factors predicting outcome in male vs female patients was identified for the first time.