Uniform Phase Permutation of Efficient Ruddlesden-Popper Perovskite Solar Cells via Binary Spacers and Single Crystal Coordination.

2D Ruddlesden-Popper perovskites (RPPs) have attracted extensive attention in recent years due to their excellent environmental stability. However, the power conversion efficiency (PCE) of RPP solar cells is much lower than that of 3D perovskite solar cells (PSCs), mainly attributed to their poor carrier transport performance and excessive heterogeneous phases. Herein, the binary spacers (n-butylammonium, BA and benzamidine, PFA) are introduced to regulate the crystallization kinetics and n-value phase distribution to form uniform phase permutation of RPP films. The study then incorporates n = 5 BA2MA4Pb5I16 memory single crystal to achieve ultrafast stepped-type carrier transport from the low n-value phases to the high n-value phases in the high-quality (BA0.75PFA0.25)2MA4Pb5I16 films. These binary spacers and single-crystal-assisted crystallization strategies produce high-quality films, leading to fast carrier extraction and significant nonradiative recombination suppression. The resulting PSC presents a champion PCE of 21.15% with an impressive open circuit voltage (VOC) of 1.26 V, which is the record high efficiency and VOC for low n-value RPP solar cells (n ≤ 5).

Activity-Independent Enzyme-Powered Amplification for Improving Signal Stability and Fidelity in Biosensing.

Enzymes are an important tool used for signal amplification in biosensing. However, traditional amplification methods based on enzymes are always dependent on their catalytic activities, so their signals fluctuate with the change of microenvironment (e.g., pH and temperature). In this work, we communicate an activity-independent enzyme-powered (AIEP) amplification strategy for biosensing to improve signal stability and fidelity. To verify this hypothesis, the monitoring of oxidative stress during drug-induced liver injury was carried out. Carboxylesterase (CEs), highly expressed in hepatic tissue, was selected as the amplification tool. A CEs configuration-matching fluorophore (CMF) was designed and screened, and a nanobeacon was fabricated by loading CMF within an O2 •--responsive polymeric micelle. Since the degradation of the nanobeacon was triggered by O2 •-, CMF was released to bind with CEs, and the fluorescence was lit by CEs-CMF configuration matching but not catalytic reaction. Results demonstrated that the oxidative stress during drug-induced liver injury could be successfully monitored, and the hepatoprotective effects of repair drugs could be evaluated by cell and in vivo imaging. This strategy is flexible for bioactive molecules by altering the responsive unit and generally accessible for pharmacological evaluation.

Importance of biopsy sample length for cancer diagnosis during trans-perineal prostate biopsy.

OBJECTIVE: To identify the factors that determine the minimum length of biopsy sample required for accurate diagnosis. MATERIALS AND METHODS: A retrospective analysis was conducted on 1202 cases that underwent rectal ultrasound-guided trans-perineal prostate biopsy (TPB) with standardized biopsy surgical procedures and pathological evaluation. Logistic regression correlation analysis and the imbalance between groups was eliminated by propensity score matching of patients' own factors between groups (positive group and negative group). ROC curve optimal threshold analysis were performed to identify the independent factors associated with cancer detection rate and the minimum length of biopsy sample required for accurate diagnosis. RESULTS: The study included 1202 cases that underwent standardized 8-18 needle initial puncture biopsies from June 2020 to October 2023. The cancer detection rate was 40.02% (481/1202), with Gleason scores of 6, 7, 8, 9, and 10 in 164, 134, 107, 67, and 9 patients, respectively. The percentage of patients with clinical significance (International Society of Urological Pathology (ISUP) ≥ 2) was 65.90% (317/481). Multivariate analysis showed that age,prostate-specific antigen(PSA), prostate volume,positive multi-parametric magnetic resonance imaging (mp-MRI) and length of biopsy samples were significant factors (P < 0.05)。Interestingly, biopsy sample length did not correlate with the prostate volume (Pearson correlation P = 0.069). ROC curve analysis: The area under the curve AUC for sample length were 0.674 and 0.664 at before and after propensity score matching,respectively; the optimal thresholds were 12.25 mm and 11.00mm at before and after propensity score matching,respectively. CONCLUSION: The independent predictors of cancer detection rate during TPB are age, PSA, prostate volume, positive mp-MRI, and sample length. Among these, sample length is the most critical indicator affecting puncture quality, and the minimum value of biopsy sample length to be obtained is 11.00mm.

Myocardial contrast echocardiography evaluation of coronary microvascular dysfunction to Predict MACEs in patients with heart failure with preserved ejection fraction follow-up.

BACKGROUND: CMD refers to the abnormalities of the tiny arteries and capillaries within the coronary artery system, which result in restricted or abnormal blood flow. CMD is an important mechanism involved in ischemic heart disease and secondary heart failure. CMD can explain left ventricular dysfunction and poor prognosis.The European Association of Cardiovascular Imaging recommends the use of MCE for the assessment of myocardial perfusion. Myocardial contrast echocardiography (MCE) is used to evaluate the accuracy of Coronary microvascular dysfunction (CMD) for predicting major adverse cardiac events (MACEs) in patients with heart failure with preserved ejection fraction (HFpEF) at follow-up. METHODS: The clinical data of 142 patients diagnosed with HFpEF in our hospital from January 2020 to January 2022 were retrospectively summarized and stratified into 77 cases (> 1) in the CMD group and 65 cases (= 1) in the non-CMD group based on the perfusion score index (PSI) of the 17 segments of the left ventricle examined by the admission MCE, and the perfusion parameters were measured at the same time, including the peak plateau intensity (A value), the curve slope of the curve rise (ßvalue) and A × ß values. At a median follow-up of 27 months till October 2023, MACEs were recorded mainly including heart failure exacerbation, revascularization, cardiac death, etc. RESULTS: Increasing age, hypertension, diabetes, and coronary artery disease in the CMD group resulted in decreased left ventricular ejection fraction (LVEF), increased plasma NT-B-type natriuretic peptide (BNP) and left ventricular global longitudinal strain (LVGLS), decreased A-values and A × ß-values, and an increased incidence of MACEs (P < 0.05). Univariate and multivariate Cox regression analyses showed that LVGLS (HR = 1.714, 95% CI = 1.289-2.279, P < 0.001) and A × ß values (HR = 0.636, 95% CI = 0.417 to 0.969, P = 0.035) were independent predictors of MACEs in patients with HFpEF. The receiver operating characteristic curve (ROC) showed that the area under the curve (AUC) of LVGLS combined with A × ß value for diagnosis of MACEs was 0.861 (95% CI = 0.761 ~ 0.961, P < 0.001), which was significantly higher than that of LVGLS or A × ß value (P < 0.05). The Kaplan-Meier survival curves showed that the cumulative survival rate in CMD group was significantly lower than non-CMD group (logrank χ2 = 6.626, P = 0.010), with the most significant difference at 20 months of follow-up. CONCLUSION: MCE can evaluate CMD semi-quantitatively and quantitatively, LVGLS combined with A × ß value has good performance in predicting the risk of developing MACEs in patients with HFpEF at 3 years of follow-up, and CMD can be used as an important non-invasive indicator for assessing clinical prognosis.

The effect of transcranial magnetic stimulation on cognitive function in post-stroke patients: a systematic review and meta-analysis.

BACKGROUND AND OBJECTIVE: Transcranial magnetic stimulation (TMS) is considered as a promising treatment option for post-stroke cognitive impairment (PSCI).Some meta-analyses have indicated that TMS can be effective in treating cognitive decline in stroke patients, but the quality of the studies included and the methodologies employed were less than satisfactory. Thus, this meta-analysis aimed to evaluate the efficacy and safety of TMS for treating post-stroke cognitive impairment. METHODS: We searched online databases like PubMed, Embase, Cochrane Library, and Web of Science to retrieve randomized controlled trials (RCTs) of TMS for the treatment of patients with PSCI. Two independent reviewers identified relevant literature, extracted purpose-specific data, and the Cochrane Risk of Bias Assessment Scale was utilized to assess the potential for bias in the literature included in this study. Stata 17.0 software was used for data analysis. RESULTS: A total of 10 studies involving 414 patients were included. The results of the meta-analysis showed that TMS was significantly superior to the control group for improving the overall cognitive function of stroke patients (SMD = 1.17, 95% CI [0.59, 1.75], I2 = 86.1%, P < 0.001). Subgroup analyses revealed that high-frequency rTMS (HF-rTMS), low-frequency rTMS (LF-rTMS), and intermittent theta burst stimulation (iTBS) all have a beneficial effect on the overall cognitive function of stroke patients. However, another subgroup analysis failed to demonstrate any significant advantage of TMS over the control group in terms of enhancing scores on the Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) and Rivermead Behavioral Memory Test (RBMT) scales. Nonetheless, TMS demonstrated the potential to enhance the recovery of activities of daily living in stroke patients, as indicated by the Modified Barthel Index (MBI) (SMD = 0.76; 95% CI [0.22, 1.30], I2 = 52.6%, P = 0.121). CONCLUSION: This meta-analysis presents evidence supporting the safety and efficacy of TMS as a non-invasive neural modulation tool for improving global cognitive abilities and activities of daily living in stroke patients. However, given the limited number of included studies, further validation of these findings is warranted through large-scale, multi-center, double-blind, high-quality randomized controlled trials. PROSPERO REGISTRATION NUMBER: CRD42022381034.

Intranasal Oxytocin Improves Interoceptive Accuracy and Heartbeat-Evoked Potentials During a Cardiac Interoceptive Task.

BACKGROUND: Interoception represents perception of the internal bodily state, which is closely associated with social/emotional processing and physical health in humans. Understanding the mechanism that underlies interoceptive processing, particularly its modulation, is therefore of great importance. Given the overlap between oxytocinergic pathways and interoceptive signaling substrates in both peripheral visceral organs and the brain, intranasal oxytocin administration is a promising approach for modulating interoceptive processing. METHODS: Using a double-blind, placebo-controlled, between-participant design, we recruited 72 healthy male participants who performed a cardiac interoceptive task during electroencephalograph and electrocardiograph recording to examine whether intranasal administration of the neuropeptide oxytocin could modulate interoceptive processing. We also collected data in a resting state to examine whether we could replicate previous findings. RESULTS: The results showed that in the interoceptive task, oxytocin increased interoceptive accuracy at the behavioral level, which was paralleled by larger heartbeat-evoked potential amplitudes in frontocentral and central regions on the neural level. However, there were no significant effects of oxytocin on electroencephalograph or electrocardiograph during resting state. CONCLUSIONS: These findings suggest that oxytocin may only have a facilitatory effect on interoceptive processing under task-based conditions. Our findings not only provide new insights into the modulation of interoceptive processing via targeting the oxytocinergic system but also provide proof-of-concept evidence for the therapeutic potential of intranasal oxytocin in mental disorders with dysfunctional interoception.

Integration of Hybridization Chain Reaction and Protein-Binding Amplification for Long-Term Imaging of Intracellular mRNA: Avoiding Signal Fluctuation.

Amplified nanoprobes based on hybridization chain reaction (HCR) have been widely developed for the detection of intracellular low abundance mRNA. However, the formed chain-like assembly decorated with fluorophore would be degraded rapidly by endogenous enzyme, resulting in failure of the long-term fluorescence imaging. To address this issue, herein, a composite signal-amplifying strategy that integrates HCR into protein-binding signal amplification (HPSA) was communicated for the in situ imaging of mRNA by avoiding signal fluctuation. Different from conventional HCR-based nanoprobes (HCR-nanoprobe), the HCR was used as the signal-triggered mode and the amplifying signal generated from in situ fluorophore-protein binding in cells, which can maintain high stability of the signal for a long time. As a proof-of-principle, a nanobeacon based on HPSA (HPSA-nanobeacon) was constructed to detect TK1 mRNA. Taking advantage of the double signal-amplifying mode, the endogenous TK1 mRNA was sensitively detected and the fluorescence signal was maintained for more than 8 h in HepG2 cells. The attempt in this work provides a new option to the current signal-amplifying strategy for sensing nucleic acid targets with high stability, significantly enhancing the acquisition of intracellular molecular information.

Halogenated Dibenzo[f,h]quinoxaline Units Constructed 2D-Conjugated Guest Acceptors for 19% Efficiency Organic Solar Cells.

Halogenation of Y-series small-molecule acceptors (Y-SMAs) is identified as an effective strategy to optimize photoelectric properties for achieving improved power-conversion-efficiencies (PCEs) in binary organic solar cells (OSCs). However, the effect of different halogenation in the 2D-structured large π-fused core of guest Y-SMAs on ternary OSCs has not yet been systematically studied. Herein, four 2D-conjugated Y-SMAs (X-QTP-4F, including halogen-free H-QTP-4F, chlorinated Cl-QTP-4F, brominated Br-QTP-4F, and iodinated I-QTP-4F) by attaching different halogens into 2D-conjugation extended dibenzo[f,h]quinoxaline core are developed. Among these X-QTP-4F, Cl-QTP-4F has a higher absorption coefficient, optimized molecular crystallinity and packing, suitable cascade energy levels, and complementary absorption with PM6:L8-BO host. Moreover, among ternary PM6:L8-BO:X-QTP-4F blends, PM6:L8-BO:Cl-QTP-4F obtains a more uniform and size-suitable fibrillary network morphology, improved molecular crystallinity and packing, as well as optimized vertical phase distribution, thus boosting charge generation, transport, extraction, and suppressing energy loss of OSCs. Consequently, the PM6:L8-BO:Cl-QTP-4F-based OSCs achieve a 19.0% efficiency, which is among the state-of-the-art OSCs based on 2D-conjugated Y-SMAs and superior to these devices based on PM6:L8-BO host (17.70%) and with guests of H-QTP-4F (18.23%), Br-QTP-4F (18.39%), and I-QTP-4F (17.62%). The work indicates that halogenation in 2D-structured dibenzo[f,h]quinoxaline core of Y-SMAs guests is a promising strategy to gain efficient ternary OSCs.

Interpretable machine learning models for predicting the incidence of antibiotic- associated diarrhea in elderly ICU patients.

BACKGROUND: Antibiotic-associated diarrhea (AAD) can prolong hospitalization, increase medical costs, and even lead to higher mortality rates. Therefore, it is essential to predict the incidence of AAD in elderly intensive care unit(ICU) patients. The objective of this study was to create a prediction model that is both interpretable and generalizable for predicting the incidence of AAD in elderly ICU patients. METHODS: We retrospectively analyzed data from the First Medical Center of the People's Liberation Army General Hospital (PLAGH) in China. We utilized the machine learning model Extreme Gradient Boosting (XGBoost) and Shapley's additive interpretation method to predict the incidence of AAD in elderly ICU patients in an interpretable manner. RESULTS: A total of 848 adult ICU patients were eligible for this study. The XGBoost model predicted the incidence of AAD with an area under the receiver operating characteristic curve (ROC) of 0.917, sensitivity of 0.889, specificity of 0.806, accuracy of 0.870, and an F1 score of 0.780. The XGBoost model outperformed the other models, including logistic regression, support vector machine (AUC = 0.809), K-nearest neighbor algorithm (AUC = 0.872), and plain Bayes (AUC = 0.774). CONCLUSIONS: While the XGBoost model may not excel in absolute performance, it demonstrates superior predictive capabilities compared to other models in forecasting the incidence of AAD in elderly ICU patients categorized based on their characteristics.

Modulating Dimensionality of 2D Perovskite Layers for Efficient and Stable 2D/3D Perovskite Photodetectors.

Two-dimensional (2D) perovskites have been widely adopted for improving the performance and stability of three-dimensional (3D) metal halide perovskite devices. However, rational manipulation of the phase composition of 2D perovskites for suitable energy level alignment in 2D/3D perovskite photodetectors (PDs) has been rarely explored. Herein, we precisely controlled the dimensionality of the 2D perovskite on CsPbI2Br films by tuning the polarity of the n-butylammonium iodide (BAI)-based solvents. In comparison to the pure n = 1 2D perovskite (ACN-BAI) formed by acetonitrile treatment, a mixture of n = 1 and n = 2 phases (IPA-BAI) generated by isopropanol (IPA) treatment guaranteed more robust defect passivation and favorable energy level alignment at the perovskite/hole transport layer interface. Consequently, the IPA-BAI PD exhibited a responsivity of 0.41 A W-1, a detectivity of 1.01 × 1013 Jones, and a linear dynamic range of 120 dB. Furthermore, the mixed-phase 2D layer effectively shielded the 3D perovskite from moisture. The IPA-BAI device retained 76% of its initial responsivity after 500 h of nonencapsulated storage at 10% relative humidity. This research provides valuable insights into the dimensional modulation of 2D perovskites for further enhancing the performance of 2D/3D perovskite PDs.

Fibroblast activation protein-sensitive polymeric nanobeacon for early diagnosis of renal fibrosis.

Early diagnosis and treatment of renal fibrosis (RF) significantly affect the clinical outcomes of chronic kidney diseases (CKDs). As the typical fibrotic ailment, RF is characterized by remodeling of the extracellular matrix, and the activation of fibroblast activation protein (FAP) plays a crucial role in the mediation of extracellular matrix protein degradation. Therefore, FAP can serve as a biomarker for RF. However, up to now, no effective tools have been reported to diagnose early-stage RF via detecting FAP. In this work, a polymeric nanobeacon integrating an FAP-sensitive amphiphilic polymer and fluorophores was proposed, which was used to diagnose early RF by sensing FAP. The FAP can be detected in the range of 0 to 200 ng/mL with a detection limit of 0.132 ng/mL. Furthermore, the fluorescence imaging results demonstrate that the polymeric nanobeacon can sensitively image fibrotic kidneys in mice with unilateral ureteral occlusion (UUO), suggesting its potential for early RF diagnosis and guidance of FAP-targeted treatments. Importantly, when employed alongside with non-invasive diagnostic techniques like magnetic resonance imaging (MRI) and serological tests, this nanobeacon exhibits excellent biocompatibility, low biological toxicity, and sustained imaging capabilities, making it a suitable fluorescent tool for diagnosing various FAP-related fibrotic conditions. To our knowledge, this study represents the first attempt to image RF in early stage by detecting FAP, offering a promising fluorescent molecular tool for diagnosing various FAP-associated diseases in the future.

Fossil evidence sheds light on sexual selection during the early evolution of birds.

The impact of sexual selection on the evolution of birds has been widely acknowledged. Although sexual selection has been hypothesized as a driving force in the occurrences of numerous morphological features across theropod evolution, this hypothesis has yet to be comprehensively tested due to challenges in identifying the sex of fossils and by the limited sample size. Confuciusornis sanctus is arguably the best-known early avialan and is represented by thousands of well-preserved specimens from the Early Cretaceous Jehol lagerstätte, which provides us with a chance to decipher the strength of sexual selection on extinct vertebrates. Herein, we present a morphometric study of C. sanctus based on the largest sample size of this taxon collected up to now. Our results indicate that the characteristic elongated paired rectrices is a sexually dimorphic trait and statistically robust inferences of the sexual dimorphism in size, shape, and allometry that have been established, providing the earliest known sexual dimorphism in avian evolution. Our findings suggest that sexual selection, in conjunction with natural selection, does act upon body size and limb length ratio in early birds, thereby promoting a deeper understanding of the role of sexual selection in large-scale phylogenetic evolution.

Glucose trend prediction model based on improved wavelet transform and gated recurrent unit.

Glucose trend prediction based on continuous glucose monitoring (CGM) data is a crucial step in the implementation of an artificial pancreas (AP). A glucose trend prediction model with high accuracy in real-time can greatly improve the glycemic control effect of the artificial pancreas and effectively prevent the occurrence of hyperglycemia and hypoglycemia. In this paper, we propose an improved wavelet transform threshold denoising algorithm for the non-linearity and non-smoothness of the original CGM data. By quantitatively comparing the mean square error (MSE) and signal-to-noise ratio (SNR) before and after the improvement, we prove that the improved wavelet transform threshold denoising algorithm can reduce the degree of distortion after the smoothing of CGM data and improve the extraction effect of CGM data features at the same time. Based on this finding, we propose a glucose trend prediction model (IWT-GRU) based on the improved wavelet transform threshold denoising algorithm and gated recurrent unit. We compared the root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination ($ {\mathrm{R}}^{2} $) of Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support vector regression (SVR), Gated Recurrent Unit (GRU) and IWT-GRU on the original CGM monitoring data of 80 patients for 7 consecutive days with different prediction horizon (PH). The results showed that the IWT-GRU model outperformed the other four models. At PH = 45 min, the RMSE was 0.5537 mmol/L, MAPE was 2.2147%, $ {\mathrm{R}}^{2} $ was 0.989 and the average runtime was only 37.2 seconds. Finally, we analyze the limitations of this study and provide an outlook on the future direction of blood glucose trend prediction.

Maternal pre-pregnancy obesity modifies the association between first-trimester thyroid hormone sensitivity and gestational Diabetes Mellitus: a retrospective study from Northern China.

BACKGROUND: Contradictory relationships have been observed between thyroid function and gestational diabetes mellitus (GDM). Previous studies have indicated that pre-pregnancy BMI (pBMI) could modify their relationships. Few studies have illustrated the role of thyroid hormone sensitivity on GDM. We aimed to explore the effect of pre-pregnancy obesity on the association between early pregnancy thyroid hormone sensitivity and GDM in euthyroid pregnant women. METHODS: This study included 1310 women with singleton gestation. Subjects were classified into pre-pregnancy obese and non-obese subgroups by pBMI levels with a cutoff of 25 kg/m2. Sensitivity to thyroid hormone was evaluated by Thyroid Feedback Quartile-Based Index (TFQI), Chinese-referenced parametric TFQI (PTFQI), TSH Index (TSHI) and Thyrotrophic T4 Resistance Index (TT4RI). The associations between these composite indices and GDM were analyzed using multivariate regression models in the two subgroups, respectively. RESULTS: In pre-pregnancy non-obese group, early pregnancy TFQI, PTFQI, TSHI and TT4RI levels were higher in subjects with incident GDM compared to those without GDM (all P < 0.05). By contrast, obese women with GDM exhibited lower levels of those indices (all P < 0.05). The occurrence of GDM were increased with rising TFQI, PTFQI, TSHI and TT4RI quartiles in non-obese women ( all P for trend < 0.05), while exhibited decreased trend across quartiles of those indices in obese women (all P for trend < 0.05). Further logistic analysis indicated contrary relationships between thyroid hormone sensitivity and the occurrence of GDM in the two groups, respectively. The OR of the fourth versus the first quartile of TFQI for GDM was 1.981 (95% CI 1.224, 3.207) in pre-pregnancy non-obese group, while was 0.131 (95% CI 0.036, 0.472) in pre-pregnancy obese group. PTFQI and TSHI yielded similar results. CONCLUSIONS: The association between maternal sensitivity to thyroid hormones during early gestation and the occurrence of GDM was modified by pre-pregnancy obesity.

Improved Deep Residual Shrinkage Network for Intelligent Interference Recognition with Unknown Interference.

In complex battlefield environments, flying ad-hoc network (FANET) faces challenges in manually extracting communication interference signal features, a low recognition rate in strong noise environments, and an inability to recognize unknown interference types. To solve these problems, one simple non-local correction shrinkage (SNCS) module is constructed. The SNCS module modifies the soft threshold function in the traditional denoising method and embeds it into the neural network, so that the threshold can be adjusted adaptively. Local importance-based pooling (LIP) is introduced to enhance the useful features of interference signals and reduce noise in the downsampling process. Moreover, the joint loss function is constructed by combining the cross-entropy loss and center loss to jointly train the model. To distinguish unknown class interference signals, the acceptance factor is proposed. Meanwhile, the acceptance factor-based unknown class recognition simplified non-local residual shrinkage network (AFUCR-SNRSN) model with the capacity for both known and unknown class recognition is constructed by combining AFUCR and SNRSN. Experimental results show that the recognition accuracy of the AFUCR-SNRSN model is the highest in the scenario of a low jamming to noise ratio (JNR). The accuracy is increased by approximately 4-9% compared with other methods on known class interference signal datasets, and the recognition accuracy reaches 99% when the JNR is -6 dB. At the same time, compared with other methods, the false positive rate (FPR) in recognizing unknown class interference signals drops to 9%.

A Reversible Fluorescent Probe for In Situ Monitoring Redox Imbalance during Mitophagy.

Mitophagy is the lysosome-dependent degradation of damaged and dysfunctional mitochondria, which is closely associated with H2O2-related redox imbalance and pathological processes. However, development of fast-responding and highly sensitive reversible fluorescent probes for monitoring of mitochondrial H2O2 dynamics is still lacking. Herein, we report a reversible fluorescent probe (M-HP) that enables real-time imaging of H2O2-related redox imbalance. In vitro studies demonstrated that M-HP had a rapid response and high sensitivity to the H2O2/GSH redox cycle, with a detection limit of 17 nM for H2O2. M-HP was applied to imaging of H2O2 fluctuation in living cells with excellent reversibility and mitochondrial targeting. M-HP reveals an increase in mitochondrial H2O2 under lipopolysaccharide stimulation and a decrease in H2O2 following the combined treatment with rapamycin. This suggests that the level of oxidative stress is significantly suppressed after the enhancement of mitophagy. The rationally designed M-HP offers a powerful tool for understanding redox imbalance during mitophagy.

A Simple Nomogram for Predicting Hospital Mortality of Patients Over 80 Years in ICU: An International Multicenter Retrospective Study.

OBJECTIVES: This study aimed to develop and validate an easy-to-use intensive care unit (ICU) illness scoring system to evaluate the in-hospital mortality for very old patients (VOPs, over 80 years old). METHODS: We performed a multicenter retrospective study based on the electronic ICU (eICU) Collaborative Research Database (eICU-CRD), Medical Information Mart for Intensive Care Database (MIMIC-III CareVue and MIMIC-IV), and the Amsterdam University Medical Centers Database (AmsterdamUMCdb). Least Absolute Shrinkage and Selection Operator regression was applied to variables selection. The logistic regression algorithm was used to develop the risk score and a nomogram was further generated to explain the score. RESULTS: We analyzed 23 704 VOPs, including 3 726 deaths (10 183 [13.5% mortality] from eICU-CRD [development set], 12 703 [17.2%] from the MIMIC, and 818 [20.8%] from the AmsterdamUMC [external validation sets]). Thirty-four variables were extracted on the first day of ICU admission, and 10 variables were finally chosen including Glasgow Coma Scale, shock index, respiratory rate, partial pressure of carbon dioxide, lactate, mechanical ventilation (yes vs no), oxygen saturation, Charlson Comorbidity Index, blood urea nitrogen, and urine output. The nomogram was developed based on the 10 variables (area under the receiver operating characteristic curve: training of 0.792, testing of 0.788, MIMIC of 0.764, and AmsterdamUMC of 0.808 [external validating]), which consistently outperformed the Sequential Organ Failure Assessment, acute physiology score III, and simplified acute physiology score II. CONCLUSIONS: We developed and externally validated a nomogram for predicting mortality in VOPs based on 10 commonly measured variables on the first day of ICU admission. It could be a useful tool for clinicians to identify potentially high risks of VOPs.

The Failure Mechanical Properties of Cemented Paste Backfill with Recycled Rubber.

Understanding the mechanical properties and failure process of cemented paste backfill with recycled rubber (RCPB) is the foundation of backfill design in underground mining. In this study, physical and mechanical tests were conducted on RCPB to obtain its mechanical property parameters, such as its uniaxial compressive strength (UCS), toughness, and peak strain. The influence of the rubber dosage on the mechanical properties of RCPB was also analyzed. In addition, the deformation behavior, fracture development, and failure process of RCPB with different rubber contents were observed using the digital image correlation (DIC) technique. The experimental results suggested that, although the UCS of RCPB is reduced as more rubber is added, its toughness and ability to absorb energy is increased. Moreover, the impact resistance of RCPB is improved by this increased toughness. With the increase in the rubber content, the deformation corresponding to the plastic yield stage of RCPB increased, which resulted in better ductility and improved impact resistance. The failure of the RCPB specimens mainly showed an "X" shape. The results of this study help us to better understand the mechanical behavior of RCPB after backfilling underground.

Monitoring H2S fluctuation during autophagic fusion of lysosomes and mitochondria using a lysosome-targeting fluorogenic probe.

Hydrogen sulfide (H2S) plays a cytoprotective role during mitophagy by detoxifying superfluous reactive oxygen species (ROS), and its concentration fluctuates in this process. However, no work has been reported to reveal the variation in H2S levels during autophagic fusion of lysosomes and mitochondria. Herein, we present a lysosome-targeted fluorogenic probe, named NA-HS, for real-time monitoring of H2S fluctuation for the first time. The newly synthesized probe exhibits good selectivity and high sensitivity (detection limit of 23.6 nM). Fluorescence imaging results demonstrated that NA-HS could image exogenous and endogenous H2S in living cells. Interestingly, the colocalization results revealed that the level of H2S was upregulated after autophagy began because of the cytoprotective effect, and was finally gradually reduced during subsequent autophagic fusion. This work not only affords a powerful fluorescence tool to monitor the variations in H2S levels during mitophagy, but also offers new insights into targeting small molecules for elaborating the complex cellular signal pathways.