Exploring the Efficacy of Hydroxybenzoic Acid Derivatives in Mitigating Jellyfish Toxin-Induced Skin Damage: Insights into Protective and Reparative Mechanisms.

The escalation of jellyfish stings has drawn attention to severe skin reactions, underscoring the necessity for novel treatments. This investigation assesses the potential of hydroxybenzoic acid derivatives, specifically protocatechuic acid (PCA) and gentisic acid (DHB), for alleviating Nemopilema nomurai Nematocyst Venom (NnNV)-induced injuries. By employing an in vivo mouse model, the study delves into the therapeutic efficacy of these compounds. Through a combination of ELISA and Western blot analyses, histological examinations, and molecular assays, the study scrutinizes the inflammatory response, assesses skin damage and repair mechanisms, and investigates the compounds' ability to counteract venom effects. Our findings indicate that PCA and DHB significantly mitigate inflammation by modulating critical cytokines and pathways, altering collagen ratios through topical application, and enhancing VEGF and bFGF levels. Furthermore, both compounds demonstrate potential in neutralizing NnNV toxicity by inhibiting metalloproteinases and phospholipase-A2, showcasing the viability of small-molecule compounds in managing toxin-induced injuries.

Assessment of disease control rate and safety of sorafenib in targeted therapy for advanced liver cancer.

OBJECTIVE: The clinical efficacy and safety of sorafenib in patients with advanced liver cancer (ALC) were evaluated based on transarterial chemoembolization (TACE). METHODS: 92 patients with ALC admitted to our hospital from May 2020 to August 2022 were randomly rolled into a control (Ctrl) group and an observation (Obs) group, with 46 patients in each. Patients in the Ctrl group received TACE treatment, while those in the Obs group received sorafenib molecular targeted therapy (SMTT) on the basis of the treatment strategy in the Ctrl group (400 mg/dose, twice daily, followed by a 4-week follow-up observation). Clinical efficacy, disease control rate (DCR), survival time (ST), immune indicators (CD3+, CD4+, CD4+/CD8+), and adverse reactions (ARs) (including mild fatigue, liver pain, hand-foot syndrome (HFS), diarrhea, and fever) were compared for patients in different groups after different treatments. RESULTS: the DCR in the Obs group (90%) was greatly higher to that in the Ctrl group (78%), showing an obvious difference (P < 0.05). The median ST in the Obs group was obviously longer and the median disease progression time (DPT) was shorter, exhibiting great differences with those in the Ctrl group (P < 0.05). Moreover, no great difference was observed in laboratory indicators between patients in various groups (P > 0.05). After treatment, the Obs group exhibited better levels in all indicators. Furthermore, the incidence of ARs in the Obs group was lower and exhibited a sharp difference with that in the Ctrl group (P < 0.05). CONCLUSION: SMTT had demonstrated good efficacy in patients with ALC, improving the DCR, enhancing the immune response of the body, and reducing the incidence of ARs, thereby promoting the disease outcome. Therefore, it was a treatment method worthy of promotion and application.

Quantum random number generation based on phase reconstruction.

Quantum random number generator (QRNG) utilizes the intrinsic randomness of quantum systems to generate completely unpredictable and genuine random numbers, finding wide applications across many fields. QRNGs relying on the phase noise of a laser have attracted considerable attention due to their straightforward system architecture and high random number generation rates. However, traditional phase noise QRNGs suffer from a 50% loss of quantum entropy during the randomness extraction process. In this paper, we propose a phase-reconstruction quantum random number generation scheme, in which the phase noise of a laser is reconstructed by simultaneously measuring the orthogonal quadratures of the light field using balanced detectors. This enables direct discretization of uniform phase noise, and the min-entropy can achieve a value of 1. Furthermore, our approach exhibits inherent robustness against the classical phase fluctuations of the unbalanced interferometer, eliminating the need for active compensation. Finally, we conducted experimental validation using commercial optical hybrid and balanced detectors, achieving a random number generation rate of 1.96 Gbps at a sampling rate of 200 MSa/s.

Machine-learning models are superior to severity scoring systems for the prediction of the mortality of critically ill patients in a tertiary medical center.

BACKGROUND: Intensive care unit (ICU) mortality prediction helps to guide therapeutic decision making for critically ill patients. Several scoring systems based on statistical techniques have been developed for this purpose. In this study, we developed a machine-learning model to predict patient mortality in the very early stage of ICU admission. METHODS: This study was performed with data from all patients admitted to the intensive care units of a tertiary medical center in Taiwan from 2009 to 2018. The patients' comorbidities, co-medications, vital signs, and laboratory data on the day of ICU admission were obtained from electronic medical records. We constructed random forest and extreme gradient boosting (XGBoost) models to predict ICU mortality, and compared their performance with that of traditional scoring systems. RESULTS: Data from 12,377 patients was allocated to training (n = 9901) and testing (n = 2476) datasets. The median patient age was 70.0 years; 9210 (74.41%) patients were under mechanical ventilation in the ICU. The areas under receiver operating characteristic curves for the random forest and XGBoost models (0.876 and 0.880, respectively) were larger than those for the Acute Physiology and Chronic Health Evaluation II score (0.738), Sequential Organ Failure Assessment score (0.747), and Simplified Acute Physiology Score II (0.743). The fraction of inspired oxygen on ICU admission was the most important predictive feature across all models. CONCLUSION: The XGBoost model most accurately predicted ICU mortality and was superior to traditional scoring systems. Our results highlight the utility of machine learning for ICU mortality prediction in the Asian population.

Transcriptome Sequencing and Mass Spectrometry Reveal Genes Involved in the Non-mendelian Inheritance-Mediated Feather Growth Rate in Chicken.

The feather growth rate in chickens included early and late feathering. We attempted to characterize the genes and pathways associated with the feather growth rate in chickens that are not in agreement with Mendelian inheritance. Gene expression profiles in the hair follicle tissues of late-feathering cocks (LC), early-feathering cocks (EC), late-feathering hens (LH), and early-feathering hens (EH) were acquired using RNA sequencing (RNA-seq), mass spectrometry (MS), and quantitative reverse transcription PCR (qRT­PCR). A total of 188 differentially expressed genes (DEGs) were ascertained in EC vs. LC and 538 DEGs were identified in EH vs. LH. We observed that 14 up-regulated genes and 9 down-regulated genes were screened both in EC vs. LC and EH vs. LH. MS revealed that 41 and 138 differentially expressed proteins (DEPs) were screened out in EC vs. LC and EH vs. LH, respectively. Moreover, these DEGs and DEPs were enriched in multiple feather-related pathways, including JAK-STAT, MAPK, WNT, TGF-ß, and calcium signaling pathways. qRT-PCR assay showed that the expression of WNT8A was decreased in LC compared with EC, while ALK and GRM4 expression were significantly up-regulated in EH relative to LH. This study helps to elucidate the potential mechanism of the feather growth rate in chickens that do not conform to genetic law.

Effects of toxin metalloproteinases from jellyfish Nemopilema nomurai nematocyst on the dermal toxicity and potential treatment of jellyfish dermatitis.

Jellyfish dermatitis is a common medical problem in many countries due to the jellyfish envenomation. However, there are no specific and targeted medications for their treatment. Here we investigated the possible therapeutic effects of metalloproteinase inhibitors on the dermal toxicity of Nemopilema nomurai nematocyst venom (NnNV), a giant venomous jellyfish from China, using the jellyfish dermatitis model, focusing on inflammatory effector molecules during jellyfish envenomation. Metalloproteinase may further stimulate inflammation by promoting oxidative stress in the organism and play key roles by activating MAPK and NF-κB, in the pathogenesis of jellyfish dermatitis. And the metalloproteinase inhibitors batimastat and EDTA disodium salt may treat the Jellyfish dermatitis by inhibiting the metalloproteinase activity in NnNV. These observations suggest that the metalloproteinase components of NnNV make a considerable contribution to dermal toxicity as the inflammation effect molecular, and metalloproteinase inhibitors can be regarded as novel therapeutic medicines in jellyfish envenomation. This study contributes to understanding the mechanism of jellyfish dermatitis and suggests new targets and ideas for the treatment of jellyfish envenomation.

Toxin metalloproteinases exert a dominant influence on pro-inflammatory response and anti-inflammatory regulation in jellyfish sting dermatitis.

Toxin metalloproteinases are the primary components responsible for various toxicities in jellyfish venom, and there is still no effective specific therapy for jellyfish stings. The comprehension of the pathogenic mechanisms underlying toxin metalloproteinases necessitates further refinement. In this study, we conducted a differential analysis of a dermatitis mouse model induced by jellyfish Nemopilema nomurai venom (NnNV) samples with varying levels of metalloproteinase activity. Through skin tissue proteomics and serum metabolomics, the predominant influence of toxin metalloproteinase activity on inflammatory response was revealed, and the signal pathway involved in its regulation was identified. In skin tissues, many membrane proteins were significantly down-regulated, which might cause tissue damage. The expression of pro-inflammatory factors was mainly regulated by PI3K-Akt signaling pathway. In serum, many fatty acid metabolites were significantly down-regulated, which might be the anti-inflammation feedback regulated by NF-κB p65 signaling pathway. These results reveal the dermatitis mechanism of toxin metalloproteinases and provide new therapeutic targets for further studies. SIGNIFICANCE: Omics is an important method to analyze the pathological mechanism and discover the key markers, which can reveal the pathological characteristics of jellyfish stings. Our research first analyzed the impact of toxin metalloproteinases on jellyfish sting dermatitis by skin proteomics and serum metabolomics. The present results suggest that inhibition of toxin metalloproteinases may be an effective treatment strategy, and provide new references for further jellyfish sting studies.

Computed Tomography-Based Radiomics Signature for Predicting Segmental Chromosomal Aberrations at 1p36 and 11q23 in Pediatric Neuroblastoma.

OBJECTIVE: This study aimed to develop and assess the precision of a radiomics signature based on computed tomography imaging for predicting segmental chromosomal aberrations (SCAs) status at 1p36 and 11q23 in neuroblastoma. METHODS: Eighty-seven pediatric patients diagnosed with neuroblastoma and with confirmed genetic testing for SCAs status at 1p36 and 11q23 were enrolled and randomly stratified into a training set and a test set. Radiomics features were extracted from 3-phase computed tomography images and analyzed using various statistical methods. An optimal set of radiomics features was selected using a least absolute shrinkage and selection operator regression model to calculate the radiomics score for each patient. The radiomics signature was validated using receiver operating characteristic curves to obtain the area under the curve and 95% confidence interval (CI). RESULTS: Eight radiomics features were carefully selected and used to compute the radiomics score, which demonstrated a statistically significant distinction between the SCAs and non-SCAs groups in both sets. The radiomics signature achieved an area under the curve of 0.869 (95% CI, 0.788-0.943) and 0.883 (95% CI, 0.753-0.978) in the training and test sets, respectively. The accuracy of the radiomics signature was 0.817 and 0.778 in the training and test sets, respectively. The Hosmer-Lemeshow test confirmed that the radiomics signature was well calibrated. CONCLUSIONS: Computed tomography-based radiomics signature has the potential to predict SCAs at 1p36 and 11q23 in neuroblastoma.

Fucoidan may treat jellyfish dermatitis by inhibiting the inflammatory effect of jellyfish venom.

Jellyfish dermatitis is a common medical problem caused by jellyfish stings. However, there are no targeted and effective medications for their treatment. Here, the biological activity of fucoidan for treatment of jellyfish dermatitis was investigated for the first time. 3 mg/mL Fucoidan attenuated the inflammatory effects of Nemopilema nomurai nematocyst venom (NnNV), including dermal toxicity and myotoxicity. Fucoidan may decrease the inflammatory effects of NnNV by downregulating MAPK and NF-κB pathways. This may be attributed to the inhibitory effect of fucoidan on metalloproteinases and phospholipase A2 (PLA2) in NnNV. 3 mg/mL fucoidan reduced the metalloproteinase activity in NnNV from 316.33 ± 20.84 U/mg to 177.33 ± 25.36 U/mg, while the inhibition of PLA2 activity in NnNV by 1 mg/mL fucoidan could reach 37.67 ± 3.42 %. Besides, external application of 3 mg/mL fucoidan can effectively alleviate the symptoms of jellyfish dermatitis. These observations suggest that fucoidan has considerable potential for treatment of jellyfish dermatitis and could be regarded as a novel medicine for jellyfish envenomation. This study provides new ideas for treatment of jellyfish envenomation and suggests evidence for the use of fucoidan in the treatment of jellyfish dermatitis as well as broadens the potential application of fucoidan in clinical practice.

[Multi-classification prediction model of lung cancer tumor mutation burden based on residual network].

Medical studies have found that tumor mutation burden (TMB) is positively correlated with the efficacy of immunotherapy for non-small cell lung cancer (NSCLC), and TMB value can be used to predict the efficacy of targeted therapy and chemotherapy. However, the calculation of TMB value mainly depends on the whole exon sequencing (WES) technology, which usually costs too much time and expenses. To deal with above problem, this paper studies the correlation between TMB and slice images by taking advantage of digital pathological slices commonly used in clinic and then predicts the patient TMB level accordingly. This paper proposes a deep learning model (RCA-MSAG) based on residual coordinate attention (RCA) structure and combined with multi-scale attention guidance (MSAG) module. The model takes ResNet-50 as the basic model and integrates coordinate attention (CA) into bottleneck module to capture the direction-aware and position-sensitive information, which makes the model able to locate and identify the interesting positions more accurately. And then, MSAG module is embedded into the network, which makes the model able to extract the deep features of lung cancer pathological sections and the interactive information between channels. The cancer genome map (TCGA) open dataset is adopted in the experiment, which consists of 200 pathological sections of lung adenocarcinoma, including 80 data samples with high TMB value, 77 data samples with medium TMB value and 43 data samples with low TMB value. Experimental results demonstrate that the accuracy, precision, recall and F1 score of the proposed model are 96.2%, 96.4%, 96.2% and 96.3%, respectively, which are superior to the existing mainstream deep learning models. The model proposed in this paper can promote clinical auxiliary diagnosis and has certain theoretical guiding significance for TMB prediction.

Impacts of Eimeria coinfection on growth performance, intestinal health and immune responses of broiler chickens.

Coccidiosis caused by Eimeria is one of the most severe chicken diseases and imposes huge economic losses to the poultry industry globally. Multi-Eimeria species coinfections are common with the most prevalent combination being mixtures of Eimeria acervulina and Eimeria tenella. Although detrimental impacts of either E. acervulina or E. tenella on chicken health are well recognized, no information is available regarding their coinfection effects so far. This study was designed to investigate the influence of coinfection with E. acervulina and E. tenella on broiler chickens. 144 one-day-old broiler chickens within each of trials (trial I or II) were divided into four groups, namely, control group (CG), E. acervulina infection group (EAIG), E. tenella infection group (ETIG) and dual (E. acervulina and E. tenella) infection group (DIG). Then, chickens were measured for weight loss, lesion scores, oocyst outputs, histological changes and expressions of pro-inflammatory (interleukin [IL]-6, IL-8 and IL-18), regulatory (IL-10 and IL-22) cytokines and Toll-like receptors (TLR; TLR2 and TLR4) as well as intestinal barrier (mucin 2 [MUC2] and fattey acid-bingding proteins 2 and 6 [FABP2 and FABP6])- and tight junction (TJ; zonula occluden-1 [ZO-1], occludin [OCLN], and claudins 1 and 5 [CLDN1 and CLDN5])-related proteins at 3, 5, 7, 10, 14 and 21 days post-infection, respectively. Our results consistently showed that although ETIG and DIG exhibited a higher level of weight loss and a more amount of oocyst excretion than EAIG, DIG had lighter lesions than EAIG in the early phase because of coinfection with E. tenella. A higher (P < 0.05) ratio of duodenal villous height to crypt depth was also observed in DIG than EAIG. Moreover, histological changes in the duodenum and cecum varied by single and dual Eimeria infections. Expressions of the intestinal barrier- and TJ-related genes of EAIG, ETIG and DIG were significantly (P < 0.05) upregulated but their levels exhibited differential changes among infected chickens. Similarly, the infected chickens showed significant (P < 0.05) inflammatory responses and higher (P < 0.05) expressions of TLRs in the intestines in comparison to CG. These results presented a comprehensive physiological, pathological and immunological characterization of E. acervulina and E. tenella coinfection in broiler chickens and also shed insights into pathogenesis of multi-coccidia coinfections.

Lipid Deposition and Progesterone Synthesis Are Increased by miR-181b-5p through RAP1B/ERK1/2 Pathway in Chicken Granulosa Cells.

Steroid hormones secreted by granulosa cells are essential for maintaining normal development of chicken follicles. Our previous sequencing data indicated that miR-181b-5p and RAS-related protein 1B (RAP1B) appeared to function in chicken granulosa cells, which was further explored in this study. The results suggested that miR-181b-5p facilitated the aggregation of lipid droplets and the synthesis of progesterone. In contrast, RAP1B astricted lipid deposition and progesterone secretion. Cotransfection of the RAP1B overexpression vector with miR-181b-5p mimic eliminated the promoting effect of miR-181b-5p. Dual-luciferase reporter assay confirmed that miR-181b-5p bound directly to the 3' untranslated region (3' UTR) of RAP1B. We also found that miR-181b-5p and RAP1B reduced and enhanced the phosphorylation levels of extracellular signal-regulated kinases 1 and 2 (ERK1/2), respectively. The application of ERK1/2 activators and inhibitors demonstrated that ERK1/2 is a negative regulator of lipid deposition and progesterone synthesis. In conclusion, we revealed that miR-181b-5p accelerated lipid deposition and progesterone synthesis through the RAP1B/ERK1/2 pathway in chicken granulosa cells. miR-181b-5p and RAP1B may serve as new biomarkers in breeding to improve chicken reproductive performance and prevent ovary-related diseases.

Molecular Regulation of Differential Lipid Molecule Accumulation in the Intramuscular Fat and Abdominal Fat of Chickens.

Reducing abdominal fat (AF) accumulation and increasing the level of intramuscular fat (IMF) simultaneously is a major breeding goal in the poultry industry. To explore the different molecular mechanisms underlying AF and IMF, gene expression profiles in the breast muscle (BM) and AF from three chicken breeds were analyzed. A total of 4737 shared DEGs were identified between BM and AF, of which 2602 DEGs were upregulated and 2135 DEGs were downregulated in the BM groups compared with the AF groups. DEGs involved in glycerophospholipid metabolism and glycerolipid metabolism were potential regulators, resulting in the difference in lipid metabolite accumulation between IMF and AF. The PPAR signaling pathway was the most important pathway involved in tissue-specific lipid deposition. Correlation analysis showed that most representative DEGs enriched in the PPAR signaling pathway, such as FABP5, PPARG, ACOX1, and GK2, were negatively correlated with PUFA-enriched glycerophospholipid molecules. Most DEGs related to glycerophospholipid metabolism, such as GPD2, GPD1, PEMT, CRLS1, and GBGT1, were positively correlated with glycerophospholipid molecules, especially DHA- and arachidonic acid (ARA)-containing glycerophospholipid molecules. This study elucidated the molecular mechanism underlying tissue-specific lipid deposition and poultry meat quality.

Research Progress of Fever with Thrombocytopenia Syndrome.

Severe fever with thrombocytopenia syndrome (SFTS) is a new infectious disease first discovered in Ta-pieh Mountains in central China in 2009. It is caused by a novel bunyavirus infection (SFTSV). Since the first discovery of SFTSV, there have been case reports and epidemiological studies on SFTS in several East Asian countries, such as South Korea, Japan, Vietnam and so on. With the rising incidence of SFTS and the rapid spread of the novel bunyavirus around the world, it is clear that the virus has a pandemic potential and may pose a threat to global public health in the future. Early studies have suggested that ticks are an important medium for the transmission of SFTSV to humans; in recent years, it has been reported that there is also human-to-human transmission. In endemic areas, potential hosts include a variety of livestock and wildlife. When people are infected with SFTV, the main clinical manifestations are high fever, thrombocytopenia, leukocytopenia, gastrointestinal symptoms, liver and kidney function damage, and even MODS, with a mortality rate of about 10-30%. This article reviews the latest progress of novel bunyavirus, including virus transmission vector, virus genotypic diversity and epidemiology, pathogenesis, clinical manifestation and treatment.

miR-136-5p/FZD4 axis is critical for Wnt signaling-mediated myogenesis and skeletal muscle regeneration.

Skeletal muscle can undergo a regenerative process in response to injury or disease to maintain muscle quality and function. Myogenesis depends on the proliferation and differentiation of myoblasts, and miRNAs can maintain the balance between them by precisely regulating many key factors in the myogenic network. Here, we found that miR-136-5p was significantly upregulated during the proliferation and differentiation of C2C12 cells. We demonstrate that miR-136-5p acts as a myogenic negative regulator during the development of mouse C2C12 myoblasts. In terms of mechanism, miR-136-5p inhibits the formation of ß-catenin/LEF/TCF DNA-binding factor transcriptional regulatory complex by targeting FZD4, a gating protein in the Wnt signaling pathway, thereby enhancing downstream myogenic factors and finally promoting myoblast proliferation and differentiation. In addition, in BaCl2 -induced muscle injury mouse model, miR-136-5p knockdown accelerated the regeneration of skeletal muscle after injury, and further led to the improvement of gastrocnemius muscle mass and muscle fiber diameter, while being suppressed by shFZD4 lentivirus infection. In summary, these results demonstrate the essential role of miR-136-5p/FZD4 axis in skeletal muscle regeneration. Given the conservation of miR-136-5p among species, miR-136-5p may be a new target for treating human skeletal muscle injury and improving the production of animal meat products.

Identification and characterization of the key lethal toxin from jellyfish Cyanea nozakii.

Jellyfish Cyanea nozakii venom is a complex mixture of various toxins, most of which are proteinous biological macromolecules and are considered to be responsible for clinical symptoms or even death after a severe sting. Previous transcriptome and proteome analysis identified hundreds of toxins in the venom, including hemolysins, C-type lectin, phospholipase A2, potassium channel inhibitor, metalloprotease, etc. However, it is not clear which toxin in the venom plays the most important role in lethality. Herein, we isolated the key lethal toxin (Letoxcn) from jellyfish Cyanea nozakii using anion exchange chromatography, size-exclusion chromatography, and cation exchange chromatography. The molecular weight of Letoxcn is ∼50 kDa with the N-terminal sequences of QADAEKVNLPVGVCV. Peptide mass fingerprinting analysis of Letoxcn shows that it may have some motifs of phospholipase, metalloproteinase, thrombin-like enzyme, potassium channel toxin, etc. However, only metalloproteinase activity but no hemolytic, PLA2, or blood coagulation activity was observed from in vitro toxicity analysis. Overall, this study uncovered and characterized the key lethal toxin in the venom of jellyfish Cyanea nozakii, which will not only help to reveal the molecule mechanism of the lethality, but also develop effective treatment like antivenom for this jellyfish sting in the future.

Whole transcriptome analysis reveals the key genes and noncoding RNAs related to follicular atresia in broilers.

Broodiness, a maternal behavior, is accompanied by the atresia of follicles and the serious degradation of poultry reproductive performance. The comparison of follicles between brooding and laying hens is usually an ideal model for exploring the regulation mechanism of follicle atresia. In this study, we selected three brooding hens and three laying hens to collect their follicles for whole transcriptome sequencing. The results demonstrated different expression patterns between the follicles of brooding hens and laying hens. In the top 10 differentially expressed genes with the highest expression, MMP10 was relatively low expressed in the follicles of brooding hens, but other nine genes were relatively highly expressed, including LRR1, RACK1, SPECC1L, ABHD2, COL6A3, RPS17, ATRN, BIRC6, PGAM1 and SPECC1L. While miR-21-3p, miR-146a-5p, miR-142-5p and miR-1b-3p were highly expressed in the follicles of brooding hen, miR-106-5p, miR-451, miR-183, miR-7, miR-2188-5p and miR-182-5p were lowly expressed in brooding hen. In addition, we identified 124 lncRNAs specifically expressed in the follicles of brooding hens and 147 lncRNAs specifically expressed in the follicles of laying hens. Our results may provide a theoretical basis for further exploration of the molecular mechanism of broodiness in broilers.

miR-138-5p promotes chicken granulosa cell apoptosis via targeting SIRT1.

Granulosa cell (GC) apoptosis is the main trigger of follicular atresia. MicroRNAs (miRNAs) are 18-22 nt RNAs whose function is primarily determined by their extended seed region and are considered to be involved in the biological functions of follicular development, including follicular atresia, folliculogenesis, and oogenesis. MiR-138-5p is known to act on chicken GCs. In this study, we found that miR-138-5p was enriched in reproductive organs, such as the uterus and ovaries. To examine whether miR-138-5p could regulate the biological process of GCs, miR-138-5p was examined by transfection of cells with a mimic or inhibitor of miR-138-5p. Expression levels of caspase-3 and caspase-9 mRNA and protein were markedly increased or decreased after transfection of the mimic or inhibitor, respectively. Furthermore, following miR-138-5p inhibition, SIRT1, one of the target genes of miR-138-5p, was found to increase the mRNA, which is correlated with the increased levels of BCL2 expression, an anti-apoptotic gene in the chicken GCs. These results suggest that miR-138-5p promotes apoptosis in chicken GCs by targeting SIRT1.

MYH1F promotes the proliferation and differentiation of chicken skeletal muscle satellite cells into myotubes.

In diploid organisms, interactions between alleles determine phenotypic variation. In previous experiments, only MYH1F was found to show both ASE (spatiotemporal allele-specific expression) and TRD (allelic transmission ratio distortion) characteristics in the pectoral muscle by comparing the genome-wide allele lists of hybrid populations (F1) of meat- and egg- type chickens. In addition, MYH1F is a member of the MYH gene family, which plays an important role in skeletal muscle and non-muscle cells of animals, but the specific expression and function of this gene in chickens are still unknown. Therefore, qRT-PCR was used to detect the expression of MYH1F in different tissues of chicken. Proliferation and differentiation of chicken skeletal muscle satellite cells (SMSCs) have been detected by transfection of MYH1F-specific small interfering RNA (siRNA). The results showed that the expression of MYH1F in chicken skeletal muscle was higher than that in other tissues. Combined with CCK-8 assay, EdU assay, immunofluorescence, and Western blot Assay, it was found that MYH1F knockdown could significantly suppress the proliferation of chicken SMSCs and depress the differentiation and fusion of the cells. These results suggest that MYH1F plays a critical role in myogenesis in poultry, which is of great significance for exploring the regulatory mechanisms of muscle development and improving animal productivity.

Development and Validation of an Energy Consumption Model for Animal Houses Achieving Precision Livestock Farming.

Indoor environmental control is usually applied in poultry farming to ensure optimum growth conditions for birds. However, these control methods represent a considerable share of total energy consumption, and the trend of applying new equipment in the future for precision livestock farming would further increase energy demand, resulting in an increase in greenhouse gas emissions and management costs. Therefore, to ensure optimum efficiency of both energy use and livestock productivity, a customized hourly model was developed in the present study to interpret and analyze the electronically collected data. The modules for estimating indoor gas concentrations were incorporated into the present model, as this has not been properly considered in previous studies. A validation test was performed in a manure-belt layer house using sensors and meters to measure the indoor environmental parameters and energy consumption. The predicted results, including indoor temperature, relative humidity, carbon dioxide and ammonia concentrations, showed good agreement with the measured data, indicating a similar overall trend with acceptable discrepancies. Moreover, the corresponding differences between the measured and simulated energy consumption for heating, tunnel ventilation and base ventilation were 13.7, 7.5, and 0.1%, respectively. The total energy demand estimated by the model showed a limited discrepancy of approximately 10.6% compared with that measured in reality. Although human factors, including inspection, cleaning, vaccination, etc., were not included in the model, the validation results still suggested that the customized model was able to accurately predict the indoor environment and overall energy consumption during poultry farming. The validated model provides a tool for poultry producers to optimize production planning and management strategies, increase the production rate of unit energy consumption and achieve precision livestock farming from an energy consumption standpoint.