Explore the vast range of titles available.

Background Advancements in synthetic genetic circuits have enabled programmable and condition-dependent control of microbial cell growth. CRISPR-Cas9-based kill switches, genetic systems that program cells to lose viability in response to specific conditions, have recently been demonstrated for bacterial cell factories but not yet in yeast. Results In this study, we present a foundational demonstration for a CRISPR-based ki ll s witch in S accharomyces cerevisiae, CRISPR KiSS. The CRISPR KiSS employs inducible CRISPR targeting essential genes to elicit growth inhibition. The activation of the KiSS system is achieved through conditional expression of a guide RNA (gRNA) upon anhydrotetracycline (ATc) induction, thereby activating CRISPR-mediated gene disruption. We demonstrate that targeting the essential genes ( ERG13, PGA3, TPI1 or CDC19) leads to severe growth inhibition upon ATc induction. Still, the current set up does not allow complete killing of the cells due to system inactivation, e.g. escape from CRISPR based cutting. We studied reasons for system inactivation and substantially improved the system by simultaneous expression of two different gRNAs. Sequencing escape mutants revealed mutations in both the gRNA sequences and target genes as potential sources of system inactivation. Conclusions This work highlights the potential of harnessing a CRISPR-based kill switch in S. cerevisiae . Cells expressing the system were able to escape growth inhibition through mutations and further optimization of the KiSS system is still needed for it to be used in various cell factory applications.

The rapid proliferation of AI-generated images in the fashion industry has created a need for systematic evaluation methods to assess garment consistency between original and AI-generated images. Conventional quantitative metrics often fail to capture fine-grained garment attributes, while human evaluation, though accurate, is costly and difficult to scale. This study proposes an automated evaluation method leveraging Vision–Language Models (VLMs) to assess garment consistency in AI-generated images. To enable systematic evaluation, we developed a garment-specific evaluation framework by operationalizing DeLong’s visual definers into 20 attributes, which were embedded into the prompt to guide the VLMs. To validate the proposed method, experiments were conducted using a real-world dataset of original fashion images paired with AI-generated ghost mannequin photography. While traditional quantitative metrics failed to effectively capture garment consistency, the proposed method demonstrated substantial alignment with human evaluation on overall garment consistency. Compared to human evaluation, the proposed method successfully identified inconsistencies across the defined attributes; however, at the attribute level, it showed higher sensitivity to color and texture but lower sensitivity to shape and line dimensions. These findings suggest that VLM-based evaluation can effectively complement existing evaluation methods by providing scalable and theoretically grounded insights.

Background Lignocellulosic biomass as feedstock has a huge potential for biochemical production. Still, efficient utilization of hydrolysates derived from lignocellulose is challenged by their complex and heterogeneous composition and the presence of inhibitory compounds, such as furan aldehydes. Using microbial consortia where two specialized microbes complement each other could serve as a potential approach to improve the efficiency of lignocellulosic biomass upgrading. Results This study describes the simultaneous inhibitor detoxification and production of lactic acid and wax esters from a synthetic lignocellulosic hydrolysate by a defined coculture of engineered Saccharomyces cerevisiae and Acinetobacter baylyi ADP1. A. baylyi ADP1 showed efficient bioconversion of furan aldehydes present in the hydrolysate, namely furfural and 5-hydroxymethylfurfural, and did not compete for substrates with S. cerevisiae , highlighting its potential as a coculture partner. Furthermore, the remaining carbon sources and byproducts of S. cerevisiae were directed to wax ester production by A. baylyi ADP1. The lactic acid productivity of S. cerevisiae was improved approximately 1.5-fold (to 0.41 ± 0.08 g/L/h) in the coculture with A. baylyi ADP1, compared to a monoculture of S. cerevisiae . Conclusion The coculture of yeast and bacterium was shown to improve the consumption of lignocellulosic substrates and the productivity of lactic acid from a synthetic lignocellulosic hydrolysate. The high detoxification capacity and the ability to produce high-value products by A. baylyi ADP1 demonstrates the strain to be a potential candidate for coculture to increase production efficiency and economics of S. cerevisiae fermentations.

We characterized the volume kinetics of crystalloid solutions (Ringer’s lactate solution and 5% dextrose water) and colloid solutions (6% tetrastarch and 10% pentastarch) by nonlinear mixed-effects modeling in healthy volunteers. We also assessed whether the bioelectrical impedance analysis parameters are significant covariates for volume kinetic parameters. Twelve male volunteers were randomly allocated to four groups, and each group received the four fluid solutions in specified sequences, separated by 1-week intervals to avoid any carryover effects. Volunteers received 40 ml/kg Ringer’s lactate solution, 20 ml/kg 5% dextrose water, 1000 ml 6% tetrastarch, and 1000 ml 10% pentastarch over 1 h. Arterial blood samples were collected to measure the hemoglobin concentration at different time points. Bioelectrical impedance spectroscopy (BIS, INBODY S10, InBody CO., LTD, Seoul, Korea) was also carried out at preset time points. In total, 671 hemoglobin-derived plasma dilution data points were used to determine the volume kinetic characteristics of each fluid. The changes in plasma dilution induced by administration of crystalloid and colloid solutions were well-described by the two-volume and one-volume models, respectively. Extracellular water was a significant covariate for the peripheral volume of distribution at baseline in the volume kinetic model of Ringer’s lactate solution. When the same amount was administered, the colloid solutions had ~4 times more plasma expansion effect than did the crystalloid solutions. Starches with larger molecular weights maintained the volume expansion effect longer than those with smaller molecular weights.

In a previous study, we developed a new analgesic index using nasal photoplethysmography (nasal photoplethysmographic index, NPI) and showed that the NPI was superior to the surgical pleth index (SPI) in distinguishing pain above numerical rating scale 3. Because the NPI was developed using data obtained from conscious patients with pain, we evaluated the performance of NPI in comparison with the SPI and the analgesia nociception index (ANI) in patients under general anaesthesia with target-controlled infusion of propofol and remifentanil. The time of nociception occurrence was defined as when the signs of inadequate anaesthesia occurred. The median values of NPI, SPI, and ANI for 1 minute from the time of the sign of inadequate anaesthesia were determined as the value of each analgesic index that represents inadequate anaesthesia. The time of no nociception was determined as 2 minutes before the onset of skin incision, and the median value for 1 minute from that time was defined as the baseline value. In total, 81 patients were included in the analysis. NPI showed good performance in distinguishing inadequate anaesthesia during propofol-remifentanil based general anaesthesia. NPI had the highest value in terms of area under the receiver operating characteristic curve, albeit without statistical significance (NPI: 0.733, SPI: 0.722, ANI: 0.668). The coefficient of variations of baseline values of NPI, SPI, and ANI were 27.5, 47.2, and 26.1, respectively. Thus, the NPI was effective for detecting inadequate anaesthesia, showing similar performance with both indices and less baseline inter-individual variability than the SPI.

Korea has one of the highest suicide rates among OECD countries, ranking first for several consecutive years, with a rate of approximately 24 deaths per 100,000 population. Understanding the association between prescription drugs and suicide attempts is crucial for developing effective suicide prevention and management strategies. This study analyzed Health Insurance Review and Assessment Service data to identify medical events preceding suicide attempts and to construct a classification model of prescribed medications using decision tree analysis. This secondary data study analyzed 1264 adult suicide attempters aged 20 to 59 years who were recruited from a pilot project for postmanagement in emergency departments conducted from March 2021 to March 2023, which may limit the generalizability of the findings. Claims data from the Health Insurance Review and Assessment Service were extracted using the specific item codes, and the drug details were obtained from the Ministry of Food and Drug Safety's pharmaceutical classification table 100-890. Of the total subjects, 65% were female and 35% male, with the highest proportion aged 20-29 years. Medications prescribed prior to suicide attempts were analyzed according to age-specific prescription patterns, with a focus on the types and classes of drugs prescribed. The classification model revealed age-specific patterns, with psychotropic medications emerging as major predictors across all age groups. These models included psychotropic medications, digestive ulcer drugs, antipyretic and analgesic agents, anticonvulsants, and respiratory system drugs, with respiratory medications emerging as the most crucial variable. In the 50s, psychotropic medications-particularly hypnotics and sedatives-appeared in all four pathways. Among these, zolpidem was most commonly prescribed for insomnia, underscoring the strong link between sleep disturbance and suicide risk. Of particular concern, nearly nine out of 10 suicide attempters were prescribed at least one medication carrying suicide-related warnings or contraindications, as noted by the Ministry of Food and Drug Safety and the U.S. Food and Drug Administration. The results highlight differences in healthcare utilization and prescribed medication patterns by age group among suicide attempters. These results can be used as foundational data for considering suicide risk during nursing assessment and diagnosis of general and psychiatric patients and developing specialized nursing strategies and management.

All metazoan organisms must reproduce and defend themselves in order to survive as individuals and as a species. These innate behaviors are so crucial that they are \"hard-wired\" into the brain during the animal's development. They are also released primarily by the olfactory stimuli detected by the AOB, which synapses into the MEA. The MEA in turn projects to the medial hypothalamic behavior control column, which contains a series of nuclei orchestrating either reproductive or defensive behaviors. These amygdalar-hypothalamic projections are topographically organized, and the sub-circuitries controlling reproduction and defense are segregated both functionally and anatomically. The topographically organized projections suggest that these neural pathways for reproduction and defense are likely genetically determined, but genes that might control their wiring have not yet been identified. Such a parallel circuit organization with very few cross-talks between the two sub-circuits also poses the problem of how rapid decisions between competing reproductive and defensive behaviors are made by organisms faced with conflicting cues. Using oligonucleotide microarrays and laser-capture microdissection, I identified that several LIM homeodomain transcription factors mark different regions of the MEA involved in either reproductive or defensive behaviors. I have characterized the projections of these neurons to the hypothalamus, using both genetically encoded anterograde and traditional retrograde tracers. I have also carried out behavioral experiments to assess their differential activations by reproductive and defensive stimuli. My results indicate that Lhx6 delineates a reproductive pathway, which involves neurons in both MEApd and BSTpr, and their projections to the three reproductive nuclei in the hypothalamic medial behavioral control column (MPN, VMHvl and PMv). Further analysis reveals, counter-intuitively, that VMHvl receives inhibitory projections from this reproductive pathway, and a convergent excitatory projection from neurons in MEApv that are activated by a predator odor. The results suggest that this point-of-convergence may serve to \"gate\" the expression of reproductive behavior, under conditions where animals are exposed to threatening stimuli. Thus, my data identifies a potential neural substrate within the hypothalamus for controlling behavioral decisions in the face of conflicting cues and a transcription factor family that may contribute to the development of this substrate.

To evaluate the feasibility of generative pre-trained transformer-4 (GPT-4) in generating structured reports (SRs) from mixed-language (English and Korean) narrative-style CT reports for pancreatic ductal adenocarcinoma (PDAC) and to assess its accuracy in categorizing PDCA resectability. This retrospective study included consecutive free-text reports of pancreas-protocol CT for staging PDAC, from two institutions, written in English or Korean from January 2021 to December 2023. Both the GPT-4 Turbo and GPT-4o models were provided prompts along with the free-text reports via an application programming interface and tasked with generating SRs and categorizing tumor resectability according to the National Comprehensive Cancer Network guidelines version 2.2024. Prompts were optimized using the GPT-4 Turbo model and 50 reports from Institution B. The performances of the GPT-4 Turbo and GPT-4o models in the two tasks were evaluated using 115 reports from Institution A. Results were compared with a reference standard that was manually derived by an abdominal radiologist. Each report was consecutively processed three times, with the most frequent response selected as the final output. Error analysis was guided by the decision rationale provided by the models. Of the 115 narrative reports tested, 96 (83.5%) contained both English and Korean. For SR generation, GPT-4 Turbo and GPT-4o demonstrated comparable accuracies (92.3% [1592/1725] and 92.2% [1590/1725], respectively; = 0.923). In the resectability categorization, GPT-4 Turbo showed higher accuracy than GPT-4o (81.7% [94/115] vs. 67.0% [77/115], respectively; = 0.002). In the error analysis of GPT-4 Turbo, the SR generation error rate was 7.7% (133/1725 items), which was primarily attributed to inaccurate data extraction (54.1% [72/133]). The resectability categorization error rate was 18.3% (21/115), with the main cause being violation of the resectability criteria (61.9% [13/21]). Both GPT-4 Turbo and GPT-4o demonstrated acceptable accuracy in generating NCCN-based SRs on PDACs from mixed-language narrative reports. However, oversight by human radiologists is essential for determining resectability based on CT findings.

Early detection of Parkinson’s disease (PD) and accurate assessment of disease progression are critical for optimizing treatment and rehabilitation. However, there is no consensus on how to effectively detect early-stage PD and classify motor symptom severity using gait analysis. This study evaluated the accuracy of machine learning models in classifying early and moderate-stages of PD based on spatiotemporal gait features at different walking speeds. A total of 178 participants were recruited, including 103 individuals with PD (61 early-stage, 42 moderate-stage) and 75 healthy controls. Participants performed a walking test on a 24-m walkway at three speeds: preferred walking speed (PWS), 20% faster (HWS), and 20% slower (LWS). Key features—walking speed at PWS, stride length at HWS, and the coefficient of variation (CV) of the stride length at LWS—achieved a classification accuracy of 78.1% using the random forest algorithm. For early PD detection, the stride length at HWS and CV of the stride length at LWS provided an accuracy of 67.3% with Naïve Bayes. Walking at PWS was the most critical feature for distinguishing early from moderate PD, with an accuracy of 69.8%. These findings suggest that assessing gait over consecutive steps under different speed conditions may improve the early detection and severity assessment of individuals with PD.

Bisphenol A (BPA) is a type of endocrine-disrupting chemical utilized in the production of plastics like epoxy resins and polycarbonate polymers. BPA exhibits weak estrogenic and potent anti-androgenic effects, and prior research has linked it to disturbances in thyroid function. This study aims to assess the potential association between early childhood exposure to urinary bisphenol A and thyroid hormone levels in pubertal children from Korea. Participants were drawn from the Ewha Birth and Growth Cohort Study, encompassing individuals who visited Ewha Women's Mokdong Hospital between 2001 and 2005. The concentration of urinary BPA was repeatedly measured for each subject at ages 3-5 years and 7-9 years. Serum levels of free triiothyronine (T3), free thyroxine (T4), and thyroid-stimulating hormone (TSH) were measured at ages 10-12 years in a subgroup of 128 out of 164 subjects who had undergone repeated BPA concentration measurements. We utilized the SAS program to analyze possible links between childhood exposure to BPA and thyroid hormone function in adolescence. Additionally, we explored how exposure to BPA during two specific periods influenced changes in thyroid hormone levels. The study observed that urinary BPA levels at ages 3-5 years were not notably linked to thyroid hormone levels in adolescents aged 10-12 years. However, BPA levels at ages 7-9 years were significantly associated with free T3 levels in girls aged 10-12 years. Conversely, exposure to BPA did not result in significant differences in thyroid hormone levels among boys. The study did not find statistically significant connections between levels of urinary BPA and the other thyroid hormones, specifically TSH and free T4. There was a significant decrease in the concentration of free T3 in girls with higher BPA concentrations. BPA exposure in childhood affects thyroid function in adolescent girls. This relationship may contribute to an increased prevalence of thyroid disorders in adolescents due to environmental influences.