Impact of Respiratory Syncytial Virus Infection on Host Functions: Implications for Antiviral Strategies.

Respiratory syncytial virus (RSV) is one of the leading causes of viral respiratory tract infection in infants, the elderly, and the immunocompromised worldwide, causing more deaths each year than influenza. Years of research into RSV since its discovery over 60 yr ago have elucidated detailed mechanisms of the host-pathogen interface. RSV infection elicits widespread transcriptomic and proteomic changes, which both mediate the host innate and adaptive immune responses to infection, and reflect RSV's ability to circumvent the host stress responses, including stress granule formation, endoplasmic reticulum stress, oxidative stress, and programmed cell death. The combination of these events can severely impact on human lungs, resulting in airway remodeling and pathophysiology. The RSV membrane envelope glycoproteins (fusion F and attachment G), matrix (M) and nonstructural (NS) 1 and 2 proteins play key roles in modulating host cell functions to promote the infectious cycle. This review presents a comprehensive overview of how RSV impacts the host response to infection and how detailed knowledge of the mechanisms thereof can inform the development of new approaches to develop RSV vaccines and therapeutics.

Inhibition of PCSK9 potentiates immune checkpoint therapy for cancer.

Despite its success in achieving the long-term survival of 10-30% of treated individuals, immune therapy is still ineffective for most patients with cancer1,2. Many efforts are therefore underway to identify new approaches that enhance such immune 'checkpoint' therapy3-5 (so called because its aim is to block proteins that inhibit checkpoint signalling pathways in T cells, thereby freeing those immune cells to target cancer cells). Here we show that inhibiting PCSK9-a key protein in the regulation of cholesterol metabolism6-8-can boost the response of tumours to immune checkpoint therapy, through a mechanism that is independent of PCSK9's cholesterol-regulating functions. Deleting the PCSK9 gene in mouse cancer cells substantially attenuates or prevents their growth in mice in a manner that depends on cytotoxic T cells. It also enhances the efficacy of immune therapy that is targeted at the checkpoint protein PD1. Furthermore, clinically approved PCSK9-neutralizing antibodies synergize with anti-PD1 therapy in suppressing tumour growth in mouse models of cancer. Inhibiting PCSK9-either through genetic deletion or using PCSK9 antibodies-increases the expression of major histocompatibility protein class I (MHC I) proteins on the tumour cell surface, promoting robust intratumoral infiltration of cytotoxic T cells. Mechanistically, we find that PCSK9 can disrupt the recycling of MHC I to the cell surface by associating with it physically and promoting its relocation and degradation in the lysosome. Together, these results suggest that inhibiting PCSK9 is a promising way to enhance immune checkpoint therapy for cancer.

Celastrol-Induced Nur77 Interaction with TRAF2 Alleviates Inflammation by Promoting Mitochondrial Ubiquitination and Autophagy.

Mitochondria play an integral role in cell death, autophagy, immunity, and inflammation. We previously showed that Nur77, an orphan nuclear receptor, induces apoptosis by targeting mitochondria. Here, we report that celastrol, a potent anti-inflammatory pentacyclic triterpene, binds Nur77 to inhibit inflammation and induce autophagy in a Nur77-dependent manner. Celastrol promotes Nur77 translocation from the nucleus to mitochondria, where it interacts with tumor necrosis factor receptor-associated factor 2 (TRAF2), a scaffold protein and E3 ubiquitin ligase important for inflammatory signaling. The interaction is mediated by an LxxLL motif in TRAF2 and results not only in the inhibition of TRAF2 ubiquitination but also in Lys63-linked Nur77 ubiquitination. Under inflammatory conditions, ubiquitinated Nur77 resides at mitochondria, rendering them sensitive to autophagy, an event involving Nur77 interaction with p62/SQSTM1. Together, our results identify Nur77 as a critical intracellular target for celastrol and unravel a mechanism of Nur77-dependent clearance of inflamed mitochondria to alleviate inflammation.

Multi-omics insights into the microbiota-gut-brain axis and cognitive improvement post-bariatric surgery.

BACKGROUND: Although numerous studies have shown that bariatric surgery results in sustained weight loss and modifications in gut microbiota composition and cognitive function, the exact underlying mechanisms are unclear. This study aimed to investigate the effects of bariatric surgery on cognitive function through the microbiota-gut-brain axis (MGBA). METHODS: Demographic data, serum samples, fecal samples, cognitive assessment scales, and resting-state functional connectivity magnetic resonance imaging (rs-fMRI) scans were obtained from 39 obese patients before and after (6 months) laparoscopic sleeve gastrectomy (LSG). PCA analysis, OPLS-DA analysis, and permutation tests were used to conduct fecal 16 S microbiota profiling, serum metabolomics, and neuroimaging analyses, and a bariatric surgery-specific rs-fMRI brain functional connectivity network was constructed. Spearman correlation analysis and Co-inertia analysis were employed to correlate significant alterations in cognitive assessment scales and resting-state functional connectivity difference networks with differential serum metabolites and 16 S microbiota data to identify key gut microbiota and serum metabolic factors. RESULTS: LSG significantly reduced the weight of obese patients, with reductions of up to 28%. Furthermore, cognitive assessment scale measurements revealed that LSG enhanced cognitive functions, including memory (HVLT, p = 0.000) and executive function (SCWT, p = 0.008). Also, LSG significantly altered gut microbiota composition (p = 0.001), with increased microbial abundance and diversity (p < 0.05). Moreover, serum metabolite levels were significantly altered, revealing intergroup differences in 229 metabolites mapped to 72 metabolic pathways (p < 0.05, VIP > 1). Spearman correlation analysis among cognitive assessment scales, gut microbiota species, and serum metabolites revealed correlations with 68 gut microbiota species and 138 serum metabolites (p < 0.05). Furthermore, pairwise correlations were detected between gut microbiota and serum metabolites (p < 0.05). Functional neuroimaging analysis revealed that LSG increased functional connectivity in cognitive-related frontotemporal networks (FPN, p < 0.01). Additionally, normalization of the default mode network (DMN) and salience network (SN) connectivity was observed after LSG (p < 0.001). Further canonical correlation and correlation analysis suggested that the cognitive-related brain network changes induced by LSG were associated with key gut microbiota species (Akkermansia, Blautia, Collinsella, Phascolarctobacterium, and Ruminococcus, p < 0.05) and neuroactive metabolites (Glycine, L-Serine, DL-Dopa, SM (d18:1/24:1(15Z), p < 0.05). CONCLUSION: These findings indicate the pathophysiological role of the microbiota-gut-brain axis in enhancing cognitive function after bariatric surgery, and the study provides a basis for clinical dietary adjustments, probiotic supplementation, and guidance for bariatric surgery, but further research is still needed. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2100049403. Registered 02 August 2021, https://www.chictr.org.cn/ .

Bacterial and clinical metabolic signatures and their interactions in obese patients post-bariatric surgery.

BACKGROUND: Obesity is a growing health concern in China, closely linked to metabolic disorders such as type 2 diabetes. Laparoscopic Sleeve Gastrectomy (LSG) is effective in promoting weight loss and improving metabolic outcomes. Emerging evidence highlights the role of gut microbiota in metabolic regulation, yet the specific alterations in gut microbiota and their association with metabolic changes post-surgery in Chinese patients remain unclear. Understanding these shifts could provide key insights into optimizing treatment strategies for metabolic improvement following bariatric surgery. METHODS: Stool samples and clinical data were collected from 30 obese patients before and 6 months after surgery. The composition of the gut microbiota was analyzed through 16S rRNA sequencing, and Spearman correlation analysis was used to determine the association between gut microbiota and clinical indicators. RESULTS: The analysis of 30 patients showed a significant decrease in Body Mass Index (BMI) (36.75 ± 4.09 kg/m2 vs 26.37 ± 3.47 kg/m2, p < 0.0001). Glucose metabolism, including Hemoglobin A1C levels, improved significantly (6.05 ± 0.96 vs 5.05 ± 0.25, p < 0.0001), and liver function as well as serum lipid levels were also notably improved. LSG increased the richness and composition of gut microbiota in obese patients post-surgery. These changes in gut microbiota were closely associated with improved clinical metabolic parameters. CONCLUSION: LSG not only significantly reduces body weight while also alleviating metabolic syndrome and comorbidities by altering gut microbiota.

Building gender-specific sexually transmitted infection risk prediction models using CatBoost algorithm and NHANES data.

BACKGROUND AND AIMS: Sexually transmitted infections (STIs) are a significant global public health challenge due to their high incidence rate and potential for severe consequences when early intervention is neglected. Research shows an upward trend in absolute cases and DALY numbers of STIs, with syphilis, chlamydia, trichomoniasis, and genital herpes exhibiting an increasing trend in age-standardized rate (ASR) from 2010 to 2019. Machine learning (ML) presents significant advantages in disease prediction, with several studies exploring its potential for STI prediction. The objective of this study is to build males-based and females-based STI risk prediction models based on the CatBoost algorithm using data from the National Health and Nutrition Examination Survey (NHANES) for training and validation, with sub-group analysis performed on each STI. The female sub-group also includes human papilloma virus (HPV) infection. METHODS: The study utilized data from the National Health and Nutrition Examination Survey (NHANES) program to build males-based and females-based STI risk prediction models using the CatBoost algorithm. Data was collected from 12,053 participants aged 18 to 59 years old, with general demographic characteristics and sexual behavior questionnaire responses included as features. The Adaptive Synthetic Sampling Approach (ADASYN) algorithm was used to address data imbalance, and 15 machine learning algorithms were evaluated before ultimately selecting the CatBoost algorithm. The SHAP method was employed to enhance interpretability by identifying feature importance in the model's STIs risk prediction. RESULTS: The CatBoost classifier achieved AUC values of 0.9995, 0.9948, 0.9923, and 0.9996 and 0.9769 for predicting chlamydia, genital herpes, genital warts, gonorrhea, and overall STIs infections among males. The CatBoost classifier achieved AUC values of 0.9971, 0.972, 0.9765, 1, 0.9485 and 0.8819 for predicting chlamydia, genital herpes, genital warts, gonorrhea, HPV and overall STIs infections among females. The characteristics of having sex with new partner/year, times having sex without condom/year, and the number of female vaginal sex partners/lifetime have been identified as the top three significant predictors for the overall risk of male STIs. Similarly, ever having anal sex with a man, age and the number of male vaginal sex partners/lifetime have been identified as the top three significant predictors for the overall risk of female STIs. CONCLUSIONS: This study demonstrated the effectiveness of the CatBoost classifier in predicting STI risks among both male and female populations. The SHAP algorithm revealed key predictors for each infection, highlighting consistent demographic characteristics and sexual behaviors across different STIs. These insights can guide targeted prevention strategies and interventions to alleviate the impact of STIs on public health.

Rapid Detection of the Anti-Tumor Drug Etoposide in Biological Samples by Using a Nanoporous-Gold-Based Electrochemical Sensor.

Monitoring etoposide is important due to its wide usage in anti-tumor therapy; however, the commonly used HPLC method is expensive and often requires complicated extraction and detection procedures. Electrochemical analysis has great application prospects because of its rapid response and high specificity, sensitivity, and efficiency with low cost and high convenience. In this study, we constructed a nanoporous gold (NPG)-modified GCE for the detection of etoposide. The electrochemical oxidation of etoposide by NPG caused a sensitive current peak at +0.27 V with good reproductivity in 50 mM of phosphate buffer (pH 7.4). The relationship between etoposide concentration and peak current was linear in the range between 0.1 and 20 µM and between 20 and 150 µM, with a detection sensitivity of 681.8 µA mM-1 cm-2 and 197.2 µA mM-1 cm-2, respectively, and a limit of detection (LOD) reaching 20 nM. The electrode had a good anti-interference ability to several common anions and cations. Spiked recovery tests in serum, urine, and fermentation broth verified the excellent performance of the sensor in terms of sensitivity, reproducibility, and specificity. This may provide a promising tool for the detection of etoposide in biological samples.

Defluorinative Multi-Functionalization of Fluoroaryl Sulfoxides Enabled by Fluorine-Assisted Temporary Dearomatization.

Owing to its unique physical properties, fluorine is often used to open up new reaction channels. In this report, we establish a cooperation of [5,5]-rearrangement and fluorine-assisted temporary dearomatization for arene multi-functionalization. Specifically, the [5,5]-rearrangement of fluoroaryl sulfoxides with ß,γ-unsaturated nitriles generates an intriguing dearomatized sulfonium species which is short-lived but exhibits unusually high electrophilicity and thus can be instantly trapped by nucleophiles and dienes at a remarkably low temperature (-95 °C) to produce four types of valuable multi-functionalized benzenes, respectively, involving appealing processes of defluorination, desulfurization, and sulfur shift. Mechanistic studies indicate that the use of fluorine on arenes not only circumvents the generally inevitable [3,3]-rearrangement but also impedes the undesired rearomatization process, thus provides a precious space for constructing and elaborating the temporarily dearomatized fluorinated sulfonium species.

Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma.

OBJECTIVES: The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for preoperative prediction of VETC and patient prognosis in hepatocellular cancer (HCC). METHODS: The study included 182 (training cohort: 128; validation cohort: 54) HCC patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Volumes of interest including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase images, from which 1316 radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the useful features. Clinical, intratumoral, peritumoral, combined radiomics, and clinical radiomics models were established using machine learning algorithms. The Kaplan-Meier survival analysis was used to assess early recurrence and progression-free survival (PFS) in the VETC + and VETC- patients. RESULTS: In the validation cohort, the area under the curves (AUCs) of radiomics models were higher than that of the clinical model using random forest (all p < 0.05). The peritumoral radiomics model (AUC = 0.972;95% confidence interval [CI]:0.887-0.998) had significantly higher AUC than intratumoral model (AUC = 0.919; 95% CI: 0.811-0.976) (p = 0.044). There were no significant differences in AUC between intratumoral or peritumoral radiomics model (PR) and combined radiomics model (p > 0.05). Early recurrence and PFS were significantly different between the PR-predicted VETC + and VETC- HCC patients (p < 0.05). PR-predicted VETC was independent predictor of early recurrence (hazard ratio [HR]: 2.08[1.31-3.28]; p = 0.002) and PFS (HR: 1.95[1.20-3.17]; p = 0.007). CONCLUSIONS: The intratumoral or peritumoral radiomics model may be useful in predicting VETC and patient prognosis preoperatively. The peritumoral radiomics model may yield an incremental value over intratumoral model. KEY POINTS: • Radiomics models are useful for predicting vessels encapsulating tumor clusters (VETC) and patient prognosis preoperatively. • Peritumoral radiomics model may yield an incremental value over intratumoral model in prediction of VETC. • Peritumoral radiomics-model-predicted VETC was an independent predictor of early recurrence and progression-free survival.

Evaluation of Different Pain-Control Procedures for Post-cardiac Surgery: A Systematic Review and Network Meta-Analysis.

OBJECTIVE: To identify superior pain-control procedures for postoperative patients who undergo cardiac surgeries. METHODS: Literature searches were conducted in globally recognized databases, including MEDLINE, EMBASE and Cochrane Central, to identify randomized controlled trials (RCTs) investigating pain-control procedures after cardiac surgeries. The parameters evaluating analgesic efficacy and postoperative recovery, namely, the pain score and ICU stay, were quantitatively pooled and estimated using Bayesian methods. The values of the surface under the cumulative ranking (SUCRA) probabilities regarding each parameter were calculated to enable the ranking of various pain-control procedures. Node-splitting analysis was performed to test the inconsistency of the main results, and the publication bias was assessed by examining the funnel-plot symmetry. RESULTS: After a detailed review, 13 RCTs containing 7 different procedures were included in the network meta-analysis. After pooling the results together, an erector spinae plane block (ESPB) and a local parasternal block (LPB) plus target-controlled infusion (TCI) presented the best analgesic effects for reducing pain at rest (SUCRA, .47) and during movement (SUCRA, .52), respectively, while the former also achieved the shortest ICU stay (SUCRA, .48). Moreover, the funnel-plot symmetries showed no inconsistencies or obvious publication bias in the current study. CONCLUSIONS: The current evidence indicates that ESPB is a potential superior analgesic strategy for post-cardiac surgery patients. To verify this conclusion further, it is imperative to obtain more high-quality evidence and conduct relevant investigations in the future.

Radiomic analysis of Gd-EOB-DTPA-enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma.

BACKGROUND: Nuclear protein Ki-67 indicates the status of cell proliferation and has been regarded as an attractive biomarker for the prognosis of HCC. The aim of this study is to investigate which radiomics model derived from different sequences and phases of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA)-enhanced MRI was superior to predict Ki-67 expression in hepatocellular carcinoma (HCC), then further to validate the optimal model for preoperative prediction of Ki-67 expression in HCC. METHODS: This retrospective study included 151 (training cohort: n = 103; validation cohort: n = 48) pathologically confirmed HCC patients. Radiomics features were extracted from the artery phase (AP), portal venous phase (PVP), hepatobiliary phase (HBP), and T2-weighted (T2W) images. A logistic regression with the least absolute shrinkage and selection operator (LASSO) regularization was used to select features to build a radiomics score (Rad-score). A final combined model including the optimal Rad-score and clinical risk factors was established. Receiver operating characteristic (ROC) curve analysis, Delong test and calibration curve were used to assess the predictive performance of the combined model. Decision cure analysis (DCA) was used to evaluate the clinical utility. RESULTS: The AP radiomics model with higher decision curve indicating added more net benefit, gave a better predictive performance than the HBP and T2W radiomic models. The combined model (AUC = 0.922 vs. 0.863) including AP Rad-score and serum AFP levels improved the predictive performance more than the AP radiomics model (AUC = 0.873 vs. 0.813) in the training and validation cohort. Calibration curve of the combined model showed a good agreement between the predicted and the actual probability. DCA of the validation cohort revealed that at a range threshold probability of 30-60%, the combined model added more net benefit compared with the AP radiomics model. CONCLUSIONS: A combined model including AP Rad-score and serum AFP levels based on enhanced MRI can preoperatively predict Ki-67 expression in HCC.

Parallel feature based calibration method for a trinocular vision sensor.

In this paper, a new method to calibrate a trinocular vision sensor is presented. A planar target with several parallel lines is utilized. The trifocal tensor of three image planes can be calculated out according to line correspondences. Compatible essential matrix between each two cameras can be obtained. Then, rotation matrix and translation matrix can be deduced base on singular value decomposition of their corresponding essential matrix. In our proposed calibration method, image rectification is carried out to remove perspective distortion. As the feature utilized is straight line, precise point to point correspondence is not necessary. Experimental results show that our proposed calibration method can obtain precise results. Moreover, the trifocal tensor can also give a strict constraint for feature matching as descripted in our previous work. Root mean square error of measured distances is 0.029 mm with regards to the view field of about 250×250 mm. As parallel feature exists widely in natural scene, our calibration method also provides a new approach for self-calibration of a trinocular vision sensor.

Nomogram to identify severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics: a multi-center study.

BACKGROUND: To develop and validate a nomogram for early identification of severe coronavirus disease 2019 (COVID-19) based on initial clinical and CT characteristics. METHODS: The initial clinical and CT imaging data of 217 patients with COVID-19 were analyzed retrospectively from January to March 2020. Two hundred seventeen patients with 146 mild cases and 71 severe cases were randomly divided into training and validation cohorts. Independent risk factors were selected to construct the nomogram for predicting severe COVID-19. Nomogram performance in terms of discrimination and calibration ability was evaluated using the area under the curve (AUC), calibration curve, decision curve, clinical impact curve and risk chart. RESULTS: In the training cohort, the severity score of lung in the severe group (7, interquartile range [IQR]:5-9) was significantly higher than that of the mild group (4, IQR,2-5) (P < 0.001). Age, density, mosaic perfusion sign and severity score of lung were independent risk factors for severe COVID-19. The nomogram had a AUC of 0.929 (95% CI, 0.889-0.969), sensitivity of 84.0% and specificity of 86.3%, in the training cohort, and a AUC of 0.936 (95% CI, 0.867-1.000), sensitivity of 90.5% and specificity of 88.6% in the validation cohort. The calibration curve, decision curve, clinical impact curve and risk chart showed that nomogram had high accuracy and superior net benefit in predicting severe COVID-19. CONCLUSION: The nomogram incorporating initial clinical and CT characteristics may help to identify the severe patients with COVID-19 in the early stage.

Selective [5,5]-Sigmatropic Rearrangement by Assembly of Aryl Sulfoxides with Allyl Nitriles.

Aromatic [5,5]-sigmatropic rearrangement is an appealing protocol for accessing 1,4-substituted arenes. However, such a protocol has not been well utilized in organic synthesis because of the difficulties in the synthesis of the substrates, selectivity issues, and limited substrate scope. Described herein is a new [5,5]-sigmatropic reaction utilizing readily available aryl sulfoxides and allyl nitriles. This reaction features mild reaction conditions, high chemo- and regioselectivity, excellent functional-group compatibility, and broad substrate scope. Computational studies suggest that the success of the reaction can be attributed to the selective electrophilic assembly of the rearrangement precursors, in which a linear -C=C=N- linkage favors [5,5]-sigmatropic rearrangement over the competitive [3,3]-sigmatropic rearrangement.

Mitochondrial protein p32/HAPB1/gC1qR/C1qbp is required for efficient respiratory syncytial virus production.

Respiratory syncytial virus (RSV) is a major cause of respiratory infections in infants and the elderly, leading to more deaths than influenza each year, but there is no antiviral or efficacious vaccine currently available. Here we examine the role in infection of the host mitochondrial protein p32 (HABP/gC1qR/C1qbp) for the first time. RSV replication as well as infectious virus production was significantly reduced by p32 siRNA knockdown, consistent with an important role for p32 in RSV infection. p32 showed distinct mitochondrial localization throughout RSV infection, but immunostaining and high resolution confocal imaging for p32 as well as MitoTracker Red and cytochrome c, revealed clear changes in mitochondrial organization in RSV infection, with perinuclear mitochondrial compaction and asymmetric distribution at 8 and 18 h post-infection, respectively. The results implicate p32 as a key host factor for RSV virus production, and bring to light the potential importance of mitochondria in RSV infection.

Induction of Nur77-dependent apoptotic pathway by a coumarin derivative through activation of JNK and p38 MAPK.

Coumarins are plant-derived natural products with a broad range of known pharmacological activities including anticancer effects. However, the molecular mechanisms by which this class of promising compounds exerts their anticancer effects remain largely unknown. We report here that a furanocoumarin named apaensin could effectively induce apoptosis of cancer cells through its activation of Jun N-terminal kinase (JNK) and p38 mitogen-activated protein kinase (MAPK). Apoptosis induction by apaensin in cancer cells was suppressed by chemical inhibitors of JNK and p38 MAPK. Inhibition of the expression of orphan nuclear receptor Nur77 by small interfering RNA (siRNA) approach also abrogated the death effect of apaensin. Molecular analysis demonstrated that JNK activation was required for the nuclear export of Nur77, a known apoptotic event in cancer cells. Although p38 MAPK activation was not involved in Nur77 nuclear export, it was essential for Nur77 mitochondrial targeting through induction of Nur77 interaction with Bcl-2, which is also known to convert Bcl-2 from an antiapoptotic to a proapoptotic molecule. Together, our results identify a new natural product that targets orphan nuclear receptor Nur77 through its unique activation of JNK and p38 MAPK and provide insight into the complex regulation of the Nur77-Bcl-2 apoptotic pathway.

p32 protein levels are integral to mitochondrial and endoplasmic reticulum morphology, cell metabolism and survival.

p32 [also known as HABP1 (hyaluronan-binding protein 1), gC1qR (receptor for globular head domains complement 1q) or C1qbp (complement 1q-binding protein)] has been shown previously to have both mitochondrial and non-mitochondrial localization and functions. In the present study, we show for the first time that endogenous p32 protein is a mitochondrial protein in HeLa cells under control and stress conditions. In defining the impact of altering p32 levels in these cells, we demonstrate that the overexpression of p32 increased mitochondrial fibrils. Conversely, siRNA-mediated p32 knockdown enhanced mitochondrial fragmentation accompanied by a loss of detectable levels of the mitochondrial fusion mediator proteins Mfn (mitofusin) 1 and Mfn2. More detailed ultrastructure analysis by transmission electron microscopy revealed aberrant mitochondrial structures with less and/or fragmented cristae and reduced mitochondrial matrix density as well as more punctate ER (endoplasmic reticulum) with noticeable dissociation of their ribosomes. The analysis of mitochondrial bioenergetics showed significantly reduced capacities in basal respiration and oxidative ATP turnover following p32 depletion. Furthermore, siRNA-mediated p32 knockdown resulted in differential stress-dependent effects on cell death, with enhanced cell death observed in the presence of hyperosmotic stress or cisplatin treatment, but decreased cell death in the presence of arsenite. Taken together, our studies highlight the critical contributions of the p32 protein to the morphology of mitochondria and ER under normal cellular conditions, as well as important roles of the p32 protein in cellular metabolism and various stress responses.

Associations between low muscle mass and clinical characteristics of health population in China.

Objectives: The primary aim of this study is to discern the association between specific clinical parameters and low muscle mass (LMM). We endeavor to elucidate the determinants of LMM and the predictive potency of individual factors. Methods: In this retrospective cross-sectional study, we encompassed 450 older adult Chinese participants (252 males and 198 females). Muscle mass quantifications were performed using bioelectrical impedance analysis. Comprehensive data encompassing demographic details (age, sex, height, and weight) and laboratory results (complete blood count, thyroid function, liver function, and renal function) were systematically recorded. Logistic regression models, coupled with receiver operating characteristic curve analytics, were employed to ascertain the variables influencing LMM and to evaluate the predictive validity of each parameter on LMM. Results: Upon confounding adjustment for age, gender, body mass index (BMI), and free thyroxine (FT4) persisted as a determinant of LMM. Specifically, individuals with an FT4 exceeding 1.105 ng/dL exhibited a 1.803-fold increased propensity for LMM relative to those with FT4 values below the specified threshold. Incorporating age, gender, BMI, and FT4 in the diagnostic algorithm enhanced the precision of LMM. The results differ between men and women. In the male population, we can still observe that FT4 has a certain value in the diagnosis of LMM, but this phenomenon is not found in the female population. Conclusions: Elevated FT4 concentrations, albeit within clinically accepted limits, are inversely associated with muscle mass. As such, FT4 could be postulated as a potential biomarker for LMM in geriatric individuals, especially in the male group.

Core-Shell PEDOT-PVDF Nanofiber-Based Ammonia Gas Sensor with Robust Humidity Resistance.

Current ammonia sensors exhibit cross-sensitivity to water vapor, leading to false alarms. We developed a core-shell nanofiber (CSNF) structure to address these issues, using conductive poly(3,4-ethylenedioxythiophene) (PEDOT) as the core and hydrophobic polyvinylidene fluoride-tetrafluoroethylene (PVDF-TrFE) as the shell. The PEDOT-PVDF CSNF, with a diameter of ~500 nm and a 300 nm thick PVDF layer, showed a superior sensitivity and humidity resistance compared to conventional PEDOT membranes for ammonia concentrations of 10-100 ppm. In humid environments, CSNF sensors outperformed membrane sensors, exhibiting a tenfold increase in performance at 51% relative humidity (RH). This study highlights the potential of CSNF sensors for practical ammonia detection, maintaining a high performance under varying humidity levels.