PPV and heavy-silicone oil injection for the treatment of eyes with RRD from inferior break(s) have a good long-term EZ continuity. ERM formation and its removal do not affect EZ.Hepatocyte nuclear factor alpha (HNF1α), endoplasmic reticulum (ER) stress, and hepatocyte apoptosis contribute to severe acute exacerbation (SAE) of liver injury. Here, we explore HNF1α-ER stress-hepatocyte apoptosis interaction in liver injury. LO2, HepG2 and SK-Hep1 cells were treated with thapsigargin (TG) or tunicamycin (TM) to induce ER stress. Carbon tetrachloride (CCl4) was used to induce acute liver injury in mice. Low-dose lipopolysaccharide (LPS) exacerbated liver injury in CCl4-induced mice. Significant apoptosis, HNF1α upregulation, and nuclear factor kappa B (NF-κB) activation were observed in human-derived hepatocytes during ER stress. Knockdown of Rela, NF-κB p65, inhibited the HNF1α upregulation. Following CCl4 treatment ER stress, apoptosis, HNF1α expression and RelA phosphorylation were significantly increased in mice. HNF1α knockdown reduced activating transcription factor 4 (ATF4) expression, and aggravated ER stress as well as hepatocyte apoptosis in vivo and in vitro. The double fluorescent reporter gene assay confirmed that HNF1α regulated the transcription of ATF4 promoter. LPS aggravated CCl4-induced liver injury and reduced HNF1α, and ATF4 expression. Therefore, in combination, HNF1α and ER stress could be mutually regulated forming a feedback loop, which helps in protecting the injured liver by down-regulating hepatocyte apoptosis. Low-dose LPS aggravates hepatocyte apoptosis and promotes the SAE of liver injury by interfering with the feedback regulation of HNF1α and ER stress in acute liver injury.We studied activity concentrations of radionuclides in the Kopački Rit Nature Park using mosses as bioindicators. This area of intact nature is at the tripoint of Croatia, Hungary, and Serbia, being located basically at the centre of the middle Danube River basin. Therefore, it can be easily affected by airborne pollution from various locations in the Middle Europe and beyond. The goal of our research was to assess whether the Park could serve as a location where any new radioactive contamination could be sensitively detected, which implied a necessity for low activity concentrations at the present time. Our gamma-ray spectrometry revealed the presence of only one anthropogenic gamma emitter, that is, 137Cs. Its activity concentration in the mosses ranged from 0.7 to 13.1 Bq kg-1, being low indeed. Another radionuclide in our focus was 210Pb. Generally, its elevated concentrations may signify ecologically undesirable human activities that involve naturally occurring radioactive matter. The activity concentration of 210Pb in the mosses was in the range from 183 to 690 Bq kg-1. This did not depart from the results of other similar studies and was again low enough for a detection of possible excess amounts of this radionuclide in the future.Preterm infants have a low level of bone mineralization compared to those born at term. The purpose of the present study was to investigate the effect of reflex locomotion therapy (RLT) on bone mineralization and growth in preterm infants and compare its effect to other physiotherapy procedures. Forty-six preterm infants born at 29-34 weeks were randomized into three groups one group received RLT (n = 17); the other group received passive movements with gentle joint compression (n = 14); and the control group received massages (n = 15). All the treatments were performed at the neonatal unit for one month. The main outcome measure was bone mineralization, which was measured using the tibial speed of sound (Tibial-SOS). All the groups were similar in terms of gestational age (31.8 ± 1.18), birth weight (1,583.41 ± 311.9), and Tibia-SOS (1,604.7 ± 27.9) at the beginning of the intervention. At the end of the study, significant differences were found among the groups in the Tibial-SOS [F(4,86) = 2.77, p = 0.049, ηp2 = 0.114] in terms of the benefit to the RLT group. In conclusion, RLT has been effective at improving Tibial-SOS levels and has been more effective than other physical therapy modalities; therefore, it could be considered an effective physiotherapeutic modality for the prevention and treatment of osteopenia from prematurity.An improved interval-valued intuitionistic fuzzy multi-attribute group decision-making method considering the risk preference of decision-makers is proposed to solve the multi-attribute group decision-making problem with interval-valued intuitionistic fuzzy numbers and the condition that the attribute weight information is completely unknown. Firstly, the decision-maker weight of each attribute is determined by combining similarity and proximity. In order to consider the influence of the decision-maker’s risk preference on the decision result and avoid the asymptotic behavior of interval-valued intuitionistic fuzzy matrix, the risk aversion coefficient of the decision-maker is introduced and combined with the determined decision-maker’s weight aggregation to form a group decision matrix. Then, the information of group decision matrix is mined, and the interval-valued intuitionistic fuzzy entropy is used to determine the attribute weight and relative weight. Based on the interval-valued intuitionistic fuzzy distance measure formula and the TODIM method, the overall superiority of each scheme relative to other schemes is obtained by calculating the superiority between schemes, and the optimal scheme is determined by comparing and sequencing. Finally, the rationality and effectiveness of the proposed method are verified by an example of mechanical assembly supplier selection decision.The human placenta represents a unique non-neuronal site of monoamine transporter expression, with pathophysiological relevance during the prenatal period. Monoamines (serotonin, dopamine, norepinephrine) are crucial neuromodulators for proper placenta functions and fetal development, including cell proliferation, differentiation, and neuronal migration. Accumulating evidence suggests that even a transient disruption of monoamine balance during gestation may lead to permanent changes in the fetal brain structures and functions, projecting into adulthood. Nonetheless, little is known about the transfer of dopamine and norepinephrine across the placental syncytiotrophoblast. Employing the method of isolated membranes from the human term placenta, here we delineate the transport mechanisms involved in dopamine and norepinephrine passage across the apical microvillous (MVM) and basal membranes. We show that the placental uptake of dopamine and norepinephrine across the mother-facing MVM is mediated via the high-affinity and low-capacity serotonin (SERT/SLC6A4) and norepinephrine (NET/SLC6A2) transporters. In the fetus-facing basal membrane, however, the placental uptake of both monoamines is controlled by the organic cation transporter 3 (OCT3/SLC22A3). Our findings thus provide insights into physiological aspects of dopamine and norepinephrine transport across both the maternal and fetal sides of the placenta. As monoamine transporters represent targets for several neuroactive drugs such as antidepressants, our findings are pharmacologically relevant to ensure the safety of drug use during pregnancy.This study aimed to investigate deep convolutional neural network- (DCNN-) based artificial intelligence (AI) model using cephalometric images for the classification of sagittal skeletal relationships and compare the performance of the newly developed DCNN-based AI model with that of the automated-tracing AI software. A total of 1574 cephalometric images were included and classified based on the A-point-Nasion- (N-) point-B-point (ANB) angle (Class I being 0-4°, Class II > 4°, and Class III  less then  0°). The DCNN-based AI model was developed using training (1334 images) and validation (120 images) sets with a standard classification label for the individual images. A test set of 120 images was used to compare the AI models. The agreement of the DCNN-based AI model or the automated-tracing AI software with a standard classification label was measured using Cohen’s kappa coefficient (0.913 for the DCNN-based AI model; 0.775 for the automated-tracing AI software). In terms of their performances, the micro-average values of the DCNN-based AI model (sensitivity, 0.94; specificity, 0.97; precision, 0.94; accuracy, 0.96) were higher than those of the automated-tracing AI software (sensitivity, 0.85; specificity, 0.93; precision, 0.85; accuracy, 0.90). With regard to the sagittal skeletal classification using cephalometric images, the DCNN-based AI model outperformed the automated-tracing AI software.Various environmental drivers influence life processes of insect vectors that transmit human disease. Life histories observed under experimental conditions can reveal such complex links; however, designing informative experiments for insects is challenging. Furthermore, inferences obtained under controlled conditions often extrapolate poorly to field conditions. Here, we introduce a pseudo-stage-structured population dynamics model to describe insect development as a renewal process with variable rates. The model permits representing realistic life stage durations under constant and variable environmental conditions. Using the model, we demonstrate how random environmental variations result in fluctuating development rates and affect stage duration. We apply the model to infer environmental dependencies from the life history observations of two common disease vectors, the southern (Culex quinquefasciatus) and northern (Culex pipiens) house mosquito. We identify photoperiod, in addition to temperature, as pivotal in regulating larva stage duration, and find that carefully timed life history observations under semi-field conditions accurately predict insect development throughout the year. The approach we describe augments existing methods of life table design and analysis, and contributes to the development of large-scale climate- and environment-driven population dynamics models for important disease vectors.In order to address the widespread concerns with food safety such as adulteration and forgery in the edible oil field, this study developed a fluorescence polarization immunoassay (FPIA) based on a monoclonal antibody in a homogeneous solution system for determination of capsaicinoids in gutter cooking oil by using chemically stable capsaicinoids as an adulteration marker. The prepared fluoresceinthiocarbamyl ethylenediamine (EDF) was coupled with capsaicinoid hapten C, and the synthesized tracer was purified by thin-layer chromatography (TLC) and showed good binding to the monoclonal antibody CPC Ab-D8. The effects of concentration of tracer and recognition components, type and pH of buffer and incubation time on the performance of FPIA were studied. The linear range (IC20 to IC80) was 3.97-97.99 ng/mL, and the half maximal inhibitory concentration (IC50) was 19.73 ng/mL, and the limit of detection (LOD) was 1.56 ng/mL. The recovery rates of corn germ oil, soybean oil and peanut blend oil were in the range of 94.