BF3 complexing phosphate/phosphonate ionic liquids: synthesis, characterization and thermophysical properties.

A new group of BF3 complexing phosphate/phosphonate ionic liquids (ILs) [Emim][X(BF3)2] (X = dimethyl phosphate, diethyl phosphate, methyl phosphonate, and ethyl phosphonate) were synthesized and characterized. Key thermophysical properties of the new complex ionic liquids, including density, viscosity, conductivity, surface tension, solid-liquid phase transition, and thermal stability were determined and compared with those of [Emim][X]. Some other important thermophysical properties such as isobaric thermal expansion coefficient, molecular volume, standard molar entropy, and lattice potential energy were obtained from measured density data, and the free volume was estimated by a linear equation presented in this article, while critical temperature, normal boiling temperature, and enthalpy of vaporization were estimated from measured surface tension and density data. Furthermore, Fragility study shows that [Emim][X(BF3)2] could be considered as metallic glass-forming liquids, while [Emim][X] could be considered as extremely fragile liquids. The ionicity of [Emim][X(BF3)2] was predicted by Walden rule, and the result shows that these ILs fit well with Walden law. The key features of these complex ILs are their extremely low glass transition (-95.33~-98.46 ℃) without melting, considerably low viscosities (33.876~58.117 mPa·s), and high values of free volume fraction (comparable to [Omim][BF4], [Emim][NTf2], and [Emim][TCB]).

A prediction model based on random survival forest analysis of the overall survival of elderly female papillary thyroid carcinoma patients: a SEER-based study.

OBJECTIVE: Papillary thyroid carcinoma (PTC) is a common malignancy whose incidence is three times greater in females than in males. The prognosis of ageing patients is poor. This research was designed to construct models to predict the overall survival of elderly female patients with PTC. METHODS: We developed prediction models based on the random survival forest (RSF) algorithm and traditional Cox regression. The data of 4539 patients were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Twelve variables were analysed to establish the models. The C-index and the Brier score were selected to evaluate the discriminatory ability of the models. Time-dependent receiver operating characteristic (ROC) curves were also drawn to evaluate the accuracy of the models. The clinical benefits of the two models were compared on the basis of the DCA curve. In addition, the Shapley Additive Explanations (SHAP) plot was used to visualize the contribution of the variables in the RSF model. RESULTS: The C-index of the RSF model was 0.811, which was greater than that of the Cox model (0.781). According to the Brier score and the area under the ROC curve (AUC), the RSF model performed better than the Cox model. On the basis of the DCA curve, the RSF model demonstrated fair clinical benefit. The SHAP plot showed that age was the most important variable contributing to the outcome of PTC in elderly female patients. CONCLUSIONS: The RSF model we developed performed better than the Cox model and might be valuable for clinical practice.

Iatrogenic skin injuries in infants admitted to neonatal intensive care units: An investigation in 22 Chinese units.

OBJECTIVE: To investigate the incidence of iatrogenic skin injuries in neonates across 22 neonatal intensive care units (NICUs) in China. DESIGN: Prospective study. SETTING: 22 NICUs in China. PATIENTS: Infants admitted to NICU. INTERVENTIONS: None. MEASUREMENTS: The "Iatrogenic Skin Injuries Data Collection Form of infants" were used to collect the data during hospitalization. MAIN RESULTS: A total of 8126 neonates who were hospitalized in 22 tertiary hospitals across 15 provinces, cities, and autonomous regions of China between December 1, 2019 and January 31, 2020 were analyzed. Five hundred and twenty-one infants had iatrogenic skin injuries, including 250 with diaper dermatitis (47.98%), 70 with physicochemical factor-related skin lesions (PCFRSIs) (13.44%), 81 with medical device-related pressure injuries (MDRPIs) (15.55%), and 69 with medical adhesive-related skin injuries (MARSIs) (13.24%), accounting for 91% of the total number of iatrogenic injuries. Among these, diaper dermatitis was closely related to the skin and feeding status. Furthermore, the risk was higher among neonates who had skin damage upon admission or were already fully fed orally. The influencing factors of MDRPIs and MARSIs were similar. They were negatively associated with gestational age and birth weight, and were closely related to the presence of various tubes. CONCLUSIONS: Diaper dermatitis, PCFRSIs, MDRPIs, and MARSIs were the four common types of iatrogenic skin injuries in newborns. The various types of iatrogenic skin injuries were influenced by varying factors. Specialized nursing measurements can reduce the likelihood of these injuries.

Electrochemical Knocking-Down of Zn Metal Clusters into Single Atoms.

Single Atoms Catalysts (SACs) have emerged as a class of highly promising heterogeneous catalysts, where the traditional bottom-up synthesis approaches often encounter considerable challenges in relation to aggregation issues and poor stability. Consequently, achieving densely dispersed atomic species in a reliable and efficient manner remains a key focus in the field. Herein, we report a new facile electrochemical knock-down strategy for the formation of SACs, whereby the metal Zn clusters are transformed into single atoms. While a defect-rich substrate plays a pivotal role in capturing and stabilizing isolated Zn atoms, the feasibility of this novel strategy is demonstrated through a comprehensive investigation, combining experimental and theoretical studies. Furthermore, when studied in exploring for potential applications, the material prepared shows a remarkable improvement of 58.21% for the Li+ storage and delivers a capacity over 300 Wh kg-1 after 500 cycles upon the transformation of Zn clusters into single atoms.

Attenuating mitochondrial dysfunction and morphological disruption with PT320 delays dopamine degeneration in MitoPark mice.

BACKGROUND: Mitochondria are essential organelles involved in cellular energy production. Changes in mitochondrial function can lead to dysfunction and cell death in aging and age-related disorders. Recent research suggests that mitochondrial dysfunction is closely linked to neurodegenerative diseases. Glucagon-like peptide-1 receptor (GLP-1R) agonist has gained interest as a potential treatment for Parkinson's disease (PD). However, the exact mechanisms responsible for the therapeutic effects of GLP-1R-related agonists are not yet fully understood. METHODS: In this study, we explores the effects of early treatment with PT320, a sustained release formulation of the GLP-1R agonist Exenatide, on mitochondrial functions and morphology in a progressive PD mouse model, the MitoPark (MP) mouse. RESULTS: Our findings demonstrate that administration of a clinically translatable dose of PT320 ameliorates the reduction in tyrosine hydroxylase expression, lowers reactive oxygen species (ROS) levels, and inhibits mitochondrial cytochrome c release during nigrostriatal dopaminergic denervation in MP mice. PT320 treatment significantly preserved mitochondrial function and morphology but did not influence the reduction in mitochondria numbers during PD progression in MP mice. Genetic analysis indicated that the cytoprotective effect of PT320 is attributed to a reduction in the expression of mitochondrial fission protein 1 (Fis1) and an increase in the expression of optic atrophy type 1 (Opa1), which is known to play a role in maintaining mitochondrial homeostasis and decreasing cytochrome c release through remodeling of the cristae. CONCLUSION: Our findings suggest that the early administration of PT320 shows potential as a neuroprotective treatment for PD, as it can preserve mitochondrial function. Through enhancing mitochondrial health by regulating Opa1 and Fis1, PT320 presents a new neuroprotective therapy in PD.

Deciphering the epidemiological dynamics: Toxoplasma gondii seroprevalence in mainland China's food animals, 2010-2023.

Background: Toxoplasma gondii (T. gondii) is a significant protozoan pathogen among food animals. Despite the threat to public health by T. gondii infections, there's limited understanding of its seroprevalence and trends in food animals across mainland China. This study aimed to estimate the seroprevalence of T. gondii infections among swine, sheep, goats, chickens, and cattle in mainland China from 2010 to 2023. Methods: We searched cross-sectional studies published between 2010 and 2023 that reported the prevalence of T. gondii in food animals from databases including PubMed, Embase, Web of Science, China Biology Medicine Disc (CBM), China National Knowledge Infrastructure (CNKI), Wanfang data, and the China Science and Technology Journal Database (CQVIP). We performed subgroup analyses to explore the impact of different factors on the seroprevalence of T. gondii. Pooled estimates of T. gondii seroprevalence were calculated with a random-effects model. Results: An analysis of 184 studies involving 211985 animals revealed a T. gondii overall seroprevalence of 15.3% (95% CI: 13.1-17.8). Although the seroprevalence of food animals across mainland China was relatively stable from 2010 to 2023, notable variations were observed across different animal types and regions (P < 0.01), along with changes in geographical distribution. Sample type, detection method, animal age, and history of abortion were identified as key risk factors for T. gondii seroprevalence. Conclusion: The study conducted a meta-analysis on the seroprevalence of T. gondii in mainland China's Food Animals from 2010 to 2023, and identified key risk factors. These findings advance our understanding of T. gondii infection dynamics, offering critical insights for developing control strategies and guiding public health policies.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging.

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Overcoming the Incompatibility Between Electrical Conductivity and Electromagnetic Transmissivity: A Graphene Glass Fiber Fabric Design Strategy.

Conventional conductive materials such as metals are crucial functional components of conductive systems in diverse electronic instruments. However, their severe intrinsic impedance mismatch with air dielectric causes strong reflection of incident electromagnetic waves, and the resulting low electromagnetic transmissivity typically interferes with surrounding electromagnetic signal communications in modern multifunction-integrated instruments. Herein, graphene glass fiber fabric (GGFF) that merges intrinsic electrical and electromagnetic properties of graphene with dielectric attributes and highly porous macrostructure of glass fiber fabric (GFF) is innovatively developed. Using a novel decoupling chemical vapor deposition growth strategy, high-quality and layer-limited graphene is prepared on noncatalytic nonmetallic GFF in a controlled manner; this is pivotal to realizing GGFF with the desired compatibility among high conductivity, low electromagnetic reflectivity, and high electromagnetic transmissivity. At the same sheet resistance over a wide range of values (250-3000 Ω·sq-1), the GGFF exhibits significantly lower electromagnetic reflectivity (by 0.42-0.51) and higher transmissivity (by 0.27-0.62) than those of its metal-based conductive counterpart (CuGFF). The material design strategy reported herein provides a constructive solution to eliminate the incompatibility between electrical conductivity and electromagnetic transmissivity faced by conventional conductive materials, spotlighting the applicability of GGFF in electric heating scenarios in radar, antenna, and stealth systems.

Construction of a Visible-Light-Response Photocatalysis-Self-Fenton Degradation System of Coupling Industrial Waste Red Mud to Resorcinol-Formaldehyde Resin.

Heterogeneous photocatalysis-self-Fenton technology is a sustainable strategy for treating organic pollutants in actual water bodies with high-fluent degradation and high mineralization capacity, overcoming the limitations of the safety risks caused by adding external iron sources and hazardous chemicals in the homogeneous Fenton reaction and injecting high-intensity energy fields in photo-Fenton reaction. Herein, a photo-self-Fenton system based on resorcinol-formaldehyde (RF) resin and red mud (RM) was established to generate hydrogen peroxide (H2O2) in situ and transform into hydroxy radical (•OH) for efficient degradation of tetracycline (TC) under visible light irradiation. The capturing experiments and electron spin resonance (ESR) confirmed that the hinge for the enhanced performance of this system is the superior H2O2 yield (499 µM) through the oxygen reduction process (ORR) of the two-step single-electron over the resin and the high concentration of •OH due to activation effect of RM. In addition, the Fe2+/Fe3+ cycles are accelerated by photoelectrons to effectively initiate the photo-self-Fenton reaction. Finally, the possible degradation pathways were proposed via liquid chromatography-mass spectrometry (LC-MS). This study provides a new idea for environmental recovery in a waste-based heterogeneous photocatalytic self-Fenton system.

A highly sensitive, long-time stable Ag/AgCl ultra-micro sensor for in situ monitoring chloride ions inside the crevice using SECM.

Tracking the variation of Cl- timely within the crevice is of great significance for comprehending the dynamic mechanism of crevice corrosion. The reported chloride ion selective electrodes are difficult to realize the long-time Cl- detection inside the confined crevice, due to their millimeter size or a relative limited lifespan. For this purpose, an Ag/AgCl ultra-micro sensor (UMS) with a radius of 12.5 µm was fabricated and optimized using laser drawing and electrodeposition techniques. Results show the AgCl film's structure is significantly impacted by the deposited current density, and further affects the linear response, life span and stability of Ag/AgCl UMS. The UMS prepared at current density of 0.1 mA/cm2 for 2 h shows a rapid response (several seconds), excellent stability and reproducibility, strong acid/alkali tolerance, sufficient linearity (R2 > 0.99), and long lifespan (86 days). Moreover, combined with the potentiometric mode of scanning electrochemical microscope (SECM), the Ag/AgCl UMS was successfully applied to monitor the in-situ radial Cl- concentration in micro-regions inside a 100 µm gap of stainless steel. The findings demonstrated that there was obvious radial difference in Cl- concentration inside the crevice, where the fastest rise in Cl- concentration was at the opening. The proposed method which combines the UMS with SECM has attractive practical applications for microzone Cl- monitoring in real time inside crevice. It may further promote the study of other localized corrosion mechanism and the development of microzone ions detection method.

Serum Interleukin-6 and Serum Ferritin Levels Are the Independent Risk Factors for Pneumonia in Elderly Patients.

Pneumonia is a common infection in elderly patients. We explored the correlations of serum interleukin-6 (IL-6) and serum ferritin (SF) levels with immune function/disease severity in elderly pneumonia patients. Subjects were allocated into the mild pneumonia (MP), severe pneumonia (SP), and normal groups, with their age/sex/body mass index/ disease course and severity/blood pressure/comorbidities/medications/prealbumin (PA)/albumin (ALB)/C-reactive protein (CRP)/procalcitonin (PCT)/smoking status documented. The disease severity was evaluated by pneumonia severity index (PSI). T helper 17 (Th17)/regulatory T (Treg) cell ratios and IL-6/SF/immunoglobulin G (IgG)/Th17 cytokine (IL-21)/Treg cytokine (IL-10)/PA/ALB levels were assessed. The correlations between these indexes/independent risk factors in elderly patients with severe pneumonia were evaluated. There were differences in smoking and CRP/PCT/ALB/PA levels among the three groups, but only CRP/ALB were different between the MP/SP groups. Pneumonia patients exhibited up-regulated Th17 cell ratio and serum IL-6/SF/IL-21/IL-10/IgG levels, down-regulated Treg cell ratio, and greater differences were noted in severe cases. Serum IL-6/SF levels were positively correlated with disease severity, immune function, and IL-21/IL-10/IgG levels. Collectively, serum IL-6 and SF levels in elderly pneumonia patients were conspicuously positively correlated with disease severity and IL-21/IL-10/IgG levels. CRP, ALB, IL-6 and SF levels were independent risk factors for severe pneumonia in elderly patients.

Gestational diabetes mellitus enhances cobalt placental transfer efficiency between mother and infant.

Background: The fetal stage is pivotal for growth and development, making it susceptible to the adverse effects of prenatal metal(loid)s exposure. This study evaluated the influence of gestational diabetes mellitus (GDM) on the placental transfer efficiency (PTE) of metal(loid)s and thus assessed the associated risks of prenatal metal(loid)s exposure.Materials and method: Designed as a case-control study, it incorporated 114 pregnant participants: 65 without complications and 49 diagnosed with GDM. We utilized inductively coupled plasma mass spectrometry to quantify seven metal(loid)s - manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), gallium (Ga), arsenic (As), and cadmium (Cd) - in both maternal venous blood and umbilical cord blood.Result: We compared metal(loid)s concentrations and their PTE in the maternal and cord blood between the two groups. Notably, Cu, Ga, As, and Co levels in the umbilical cord blood of the GDM group (657.9 ± 167.2 µg/L, 1.23 ± 0.34 µg/L, 5.19 ± 2.58 µg/L, 1.09 ± 2.03 µg/L) surpassed those of the control group, with PTE of Co showing a marked increase in GDM group (568.8 ± 150.4 µg/L, 1.05 ± 0.31 µg/L, 4.09 ± 2.54 µg/L, 0.47 ± 0.91 µg/L), with PTE of Co showing a marked increase in GDM group (p < 0.05). The PTE of Ni exhibited a reduction in the GDM group relative to the control group, yet this decrease did not reach statistical significance.Conclusion: This study indicates that GDM can influence the placental transfer efficiency of certain metal(loid)s, leading to higher concentrations of Co, Cu, Ga, and As in the umbilical cord blood of the GDM group. The marked increase in the PTE of Co suggests a potential link to placental abnormal angiogenesis due to GDM.

Numerical analysis of on-chip acousto-optic modulators for visible wavelengths.

On-chip acousto-optic modulators that operate at an optical wavelength of 780 nm and a microwave frequency of 6.835 GHz are proposed. The modulators are based on a lithium-niobate-on-sapphire platform and efficiently excite surface acoustic waves and exhibit strong interactions with tightly confined optical modes in waveguides. In particular, a high-efficiency phase modulator and single-sideband mode converter are designed. We found that for both microwave and optical wavelengths below 1 µm, the interactions at the cross-sections of photonic waveguides are sensitive to the waveguide width and are significantly different from those in previous studies. Our designed devices have small footprints and high efficiencies, making them suitable for controlling rubidium atoms and realizing hybrid photonic-atomic chips. Furthermore, our devices have the potential to extend the acousto-optic modulators to other visible wavelengths for other atom transitions and for visible light applications, including imaging and sensing.

Enhanced identification and localization of metabolites in Scutellariae Radix using ion mobility enabled MALDI-Q-TOF/MS imaging.

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Targeting ATP-binding site of WRN Helicase: Identification of novel inhibitors through pocket analysis and Molecular Dynamics-Enhanced virtual screening.

WRN helicase is a critical protein involved in maintaining genomic stability, utilizing ATP hydrolysis to dissolve DNA secondary structures. It has been identified as a promising synthetic lethal target for microsatellite instable (MSI) cancers. However, few WRN helicase inhibitors have been discovered, and their potential binding sites remain unexplored. In this study, we analyzed potential binding sites for WRN inhibitors and focused on the ATP-binding site for screening new inhibitors. Through molecular dynamics-enhanced virtual screening, we identified two compounds, h6 and h15, which effectively inhibited WRN's helicase and ATPase activity in vitro. Importantly, these compounds selectively targeted WRN's ATPase activity, setting them apart from other non-homologous proteins with ATPase activity. In comparison to the homologous protein BLM, h6 exhibits some degree of selectivity towards WRN. We also investigated the binding mode of these compounds to WRN's ATP-binding sites. These findings offer a promising strategy for discovering new WRN inhibitors and present two novel scaffolds, which might be potential for the development of MSI cancer treatment.

Multifunctional thiolated chitosan/puerarin composite hydrogels with pH/glutathione dual responsiveness for potential drug carriers.

Puerarin (PUE), a natural and biologically active isoflavone extracted from Chinese medicine Pueraria lobata, can self-assemble to form a hydrogel without other chemical modifications. However, although PUE hydrogel has pH responsivity, but it is difficult to adapt to the changeable pathological environment. Therefore, thiolated chitosan (TCS) is synthesized and hybridized with PUE hydrogel to prepare TCS10/PUE composite hydrogel. The results of rheological measurement showed that the resultant composite hydrogels inherited the low loss performance of TCS hydrogel, which means that they have stronger elasticity. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images displayed that TCS10/PUE composite hydrogel has a fibrous-network structure. X-Ray Diffractometer (XRD) and Fourier transform infrared spectroscopy (FT-IR) proved the existence of hydrogen bonds and disulfide bonds in the formation of composite hydrogel. Degradation experiment showed that TCS10/PUE composite hydrogels have pH and glutathione (pH/GSH) dual sensitivity. Furthermore, TCS10/PUE composite hydrogels exhibited multi-functionality including thixotropy, cytocompatibility, antibacterial and anti-inflammatory properties. Berberine chloride hydrate (BCH) was further used as a model drug for in vitro release study. BCH and PUE could be released cooperatively under pH/GSH dual responsivity. These results indicated that the resultant composite hydrogel has eminent pH/GSH dual responsivity and could act as a potential new intelligent drug carrier.

A novel breast cancer image classification model based on multiscale texture feature analysis and dynamic learning.

Assistive medical image classifiers can greatly reduce the workload of medical personnel. However, traditional machine learning methods require large amounts of well-labeled data and long learning times to solve medical image classification problems, which can lead to high training costs and poor applicability. To address this problem, a novel unsupervised breast cancer image classification model based on multiscale texture analysis and a dynamic learning strategy for mammograms is proposed in this paper. First, a gray-level cooccurrence matrix and Tamura coarseness are used to transfer images to multiscale texture feature vectors. Then, an unsupervised dynamic learning mechanism is used to classify these vectors. In the simulation experiments with a resolution of 40 pixels, the accuracy, precision, F1-score and AUC of the proposed method reach 91.500%, 92.780%, 91.370%, and 91.500%, respectively. The experimental results show that the proposed method can provide an effective reference for breast cancer diagnosis.

Bioinformatics integration reveals key genes associated with mitophagy in myocardial ischemia-reperfusion injury.

BACKGROUND: Myocardial ischemia is a prevalent cardiovascular disorder associated with significant morbidity and mortality. While prompt restoration of blood flow is essential for improving patient outcomes, the subsequent reperfusion process can result in myocardial ischemia-reperfusion injury (MIRI). Mitophagy, a specialized autophagic mechanism, has consistently been implicated in various cardiovascular disorders. However, the specific connection between ischemia-reperfusion and mitophagy remains elusive. This study aims to elucidate and validate central mitophagy-related genes associated with MIRI through comprehensive bioinformatics analysis. METHODS: We acquired the microarray expression profile dataset (GSE108940) from the Gene Expression Omnibus (GEO) and identified differentially expressed genes (DEGs) using GEO2R. Subsequently, these DEGs were cross-referenced with the mitophagy database, and differential nucleotide sequence analysis was performed through enrichment analysis. Protein-protein interaction (PPI) network analysis was employed to identify hub genes, followed by clustering of these hub genes using cytoHubba and MCODE within Cytoscape software. Gene set enrichment analysis (GSEA) was conducted on central genes. Additionally, Western blotting, immunofluorescence, and quantitative polymerase chain reaction (qPCR) analyses were conducted to validate the expression patterns of pivotal genes in MIRI rat model and H9C2 cardiomyocytes. RESULTS: A total of 2719 DEGs and 61 mitophagy-DEGs were identified, followed by enrichment analyses and the construction of a PPI network. HSP90AA1, RPS27A, EEF2, EIF4A1, EIF2S1, HIF-1α, and BNIP3 emerged as the seven hub genes identified by cytoHubba and MCODE of Cytoscape software. Functional clustering analysis of HIF-1α and BNIP3 yielded a score of 9.647, as determined by Cytoscape (MCODE). In our MIRI rat model, Western blot and immunofluorescence analyses confirmed a significant elevation in the expression of HIF-1α and BNIP3, accompanied by a notable increase in the ratio of LC3II to LC3I. Subsequently, qPCR confirmed a significant upregulation of HIF-1α, BNIP3, and LC3 mRNA in the MIRI group. Activation of the HIF-1α/BNIP3 pathway mediates the regulation of the degree of Mitophagy, thereby effectively reducing apoptosis in rat H9C2 cardiomyocytes. CONCLUSIONS: This study has identified seven central genes among mitophagy-related DEGs that may play a pivotal role in MIRI, suggesting a correlation between the HIF-1α/BNIP3 pathway of mitophagy and the pathogenesis of MIRI. The findings highlight the potential importance of mitophagy in MIRI and provide valuable insights into underlying mechanisms and potential therapeutic targets for further exploration in future studies.

Effect of Day Length on Growth and Gonadal Development in Meishan Male Pigs.

Day length is a critical environmental factor for regulating animal growth and development. This study aimed to investigate the effects of different day lengths on the developmental changes of growth parameters, testicular sizes, testosterone secretion in Meishan male pigs, and steroidogenesis proteins and melatonin receptors. Fourteen Meishan male pigs (10 weeks (wks) of age) with the same parity, paired in litter and body weight (BW), were evenly allocated into a short-day-length group (SDL, 10 light/14 dark) and long-day-length group (LDL, 14 light/10 dark). After 12 wks of the experiment, the LDL-treated boars had more lying time and less exploring time. The LDL treatment led to significant increases in body height, chest circumference, testicular length, testicular weight, crude protein digestibility, and fecal testosterone at the 10th and 12th wks of the experiment, and cortisol at the 10th wk, compared to the SDL treatment, with no differences in the final BW, testicular width, and epididymis weight. Furthermore, the LDL treatment significantly increased the protein levels of melatonin receptor 1b (MT2), aromatase (CYP19), and steroidogenic factor 1 (SF1) in the testis, with no differences in the protein levels of melatonin receptor 1a (MT1), steroidogenic acute regulatory (StAR), 3ß-hydroxysteroid dehydrogenase (3ß-HSD), and cholesterol side-chain cleavage enzyme (P450scc). The present study suggests that day length has an effect on the growth and gonadal development in male pigs maybe via MT2 and influences steroid synthesis and secretion in the testis. Therefore, proper day length should be considered in male pig breeding.

Improved beluga whale optimization algorithm based cluster routing in wireless sensor networks.

Cluster routing is a critical routing approach in wireless sensor networks (WSNs). However, the uneven distribution of selected cluster head nodes and impractical data transmission paths can result in uneven depletion of network energy. For this purpose, we introduce a new routing strategy for clustered wireless sensor networks that utilizes an improved beluga whale optimization algorithm, called tCBWO-DPR. In the selection process of cluster heads, we introduce a new excitation function to evaluate and select more suitable candidate cluster heads by establishing the correlation between the energy of node and the positional relationship of nodes. In addition, the beluga whale optimization (BWO) algorithm has been improved by incorporating the cosine factor and t-distribution to enhance its local and global search capabilities, as well as to improve its convergence speed and ability. For the data transmission path, we use Prim's algorithm to construct a spanning tree and introduce DPR for determining the optimal route between cluster heads based on the correlation distances of cluster heads. This effectively shortens the data transmission path and enhances network stability. Simulation results show that the improved beluga whale optimization based algorithm can effectively improve the survival cycle and reduce the average energy consumption of the network.