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BackgroundPropylene glycol monomethyl ether (PGME) is a widely used organic solvent. It exists in the form of two isomers in the workplace, which will cause adverse effects such as eye and upper respiratory tract irritation in workers. However, there is still a lack of standard detection methods for simultaneous detection of two isomers of PGME in China. ObjectiveTo establish a solvent desorption-gas chromatographic method for two isomers of PGME [1-methoxy-2-propanol (α-PGME), 2-methoxy-1-propanol (β-PGME)] in workplace air. MethodsA method of solvent desorption-gas chromatography for α-PGME and β-PGME in workplace air were proposed. Air samples were collected with solvent desorption activated carbon tubes, desorbed using a desorption solution of dichloromethane/methanol (85:15), and then separated on a free fatty acid phase (FFAP) fused silica capillary chromatography column , detected with a flame ionization detector (FID), and quantified by peak area. Standard evaluation protocol was followed to obtain key indicators: standard curve, limit of detection, lower limit of quantification, relative standard deviation (RSD) that measures precision, and spiked recovery of sample solutions that measures accuracy. Desorption efficiency, sampling efficiency, and adsorption capacity tests were conducted, sample stability was evaluated using spiked activated carbon tube preservation test, and interference test was also assessed. The developed method was then applied to field air sample testing. ResultsIn this method, using dichloromethane/methanol (85:15) as the sample desorption solution, the quantitative detection ranges of α-PGME and β-PGME were 0.95-923.0 μg·mL−1 and 0.97-912.0 μg·mL−1 with both correlation coefficients of 0.999 9, the method limits of detection were 0.28 µg·mL−1 and 0.29 µg·mL−1, and the lower limits of quantification were 0.95 µg·mL−1 and 0.97 µg·mL1, respectively. The lowest concentrations detected were both 0.19 mg·m−3, and the lowest concentrations quantified were 0.63 mg·m−3 and 0.65 mg·m−3, respectively, under the conditions of sampling volume of 1.5 L and the volume of desorption solution of 1.0 mL. The intra-batch precisions for α-PGME and β-PGME were 2.8%-4.9% and 2.8%-5.1%, the inter-batch precisions were 4.2%-5.7% and 4.5%-5.9%, the spiked recoveries were 98.8%-100.3% and 96.4%-102.9%, and the desorption efficiencies were 92.7%-97.3% and 92.2%-98.1%, respectively. The average sampling efficiency was 100%, and the samples could be stored at room temperature (25-30 ℃) for at least 7 d and at 4 ℃ for at least 15 d. The adsorption capacities of the activated carbon sampling tube for α-PGME and β-PGME were greater than 13.9 mg and 2.7 mg (100 mg of activated carbon adsorbent), respectively. Possible co-existing components in workplace did not interfere with the determination of α-PGME and β-PGME. The short-time exposure concentrations of α-PGME and β-PGME in the spray painting unit of an automobile manufacturing company were determined to be 18.69 mg·m−3 and 2.19 mg·m−3, and the time-weighted average concentrations were 6.03 mg·m−3 and 1.08 mg·m−3 respectively. ConclusionThis method is accurate, precise and suitable for on-site monitoring of the two isomers of PGME in workplace air.

ABSTRACT: The distribution of mineral elements in milk is crucial for their absorption and utilization, however, there has been limited attention given to the status of mineral elements in goat milk. In this study, goat milk was collected at 4 lactation periods (1–3, 90, 150, 240 d) and separated into 4 fractions (fat, casein, whey, and aqueous phase). The concentrations of Mg, Ca, Na, K, Zn, Fe, Cu, Mn, Co, Ni, Mo, and Cr in 4 fractions were analyzed using an inductively coupled plasma emission spectrometer. Our findings reveal that Ca, Zn, Fe, Cu, Mn, and Cr exhibit the highest levels in casein, while Mo demonstrates the highest content in whey. Additionally, Mg, Na, K, and Ni display the highest concentrations in the aqueous phase. Specifically, the contents of Ca, Cu and Fe in casein decrease from 1–3 to 150 d of lactation but increase from 150 to 240 d of lactation. Furthermore, the content of Mg in the aqueous phase decreases from 1–3 to 90 d of lactation but increases from 90 to 240 d of lactation. The content of Na and K in the aqueous phase decreases from 1–3 to 150 d of lactation. Notably, the content of Mo in whey increases from 1–3 to 150 d of lactation and decreases from 150 to 240 d. Our research contributes to the advancement of understanding the bioavailability of mineral elements in goat milk.

The importance of food components to potential benefits and risks to human health is gradually being consumer awareness. Milk is an important part of the lipid content of the human diet, and there are few detailed reports on the fatty acid (FA) profiles of retail milk. In the study, we developed a gas chromatography–mass spectrometry (GC-MS) method to simultaneously determine 82 FAs, including 11 even-chain saturated FAs, 10 odd-chain saturated FAs, 9 branched-chain saturated FAs, 30 monounsaturated FAs, and 22 polyunsaturated FAs; this was applied to analyze samples (186 samples) of commercially available milk from 22 provinces throughout China and to evaluate the nutritional value of these samples based on FA-related indices. The results showed that the overall composition of milk FAs among the different regions was numerically similar, and minor FAs showed few differences. When considering the retail milk FA composition and dairy fat intake in China, regional variations have a limited impact on FA consumption. Moreover, milk accounts for approximately one-third and

The milk fat globule membrane (MFGM) is a complex tri-layer membrane that wraps droplets of lipids in milk. In recent years, it has attracted widespread attention due to its excellent bioactive functions and nutritional value. MFGM contains a diverse array of bioactive lipids, including cholesterol, phospholipids, and sphingolipids, which play pivotal roles in mediating the bioactivity of the MFGM. We sequentially summarize the main lipid types in the MFGM in this comprehensive review and outline the characterization methods used to employ them. In this comprehensive review, we sequentially describe the types of major lipids found in the MFGM and outline the characterization methods employed to study them. Additionally, we compare the structural disparities among glycerophospholipids, sphingolipids, and gangliosides, while introducing the formation of lipid rafts facilitated by cholesterol. The focus of this review revolves around an extensive evaluation of the current research on lipid isolates from the MFGM, as well as products containing MFGM lipids, with respect to their impact on human health. Notably, we emphasize the clinical trials encompassing a large number of participants. The summarized bioactive functions of MFGM lipids encompass the regulation of human growth and development, influence on intestinal health, inhibition of cholesterol absorption, enhancement of exercise capacity, and anticancer effects. By offering a comprehensive overview, the aim of this review is to provide valuable insights into the diverse biologically active functions exhibited by lipids in the MFGM.

Abstract Background Antibiotic-associated diarrhea (AAD) is a risk factor for exacerbating the outcome of critically ill patients. Dysbiosis induced by the exposure to antibiotics reveals the potential therapeutic role of fecal microbiota transplantation (FMT) in these patients. Herein, we aimed to evaluate the safety and potential benefit of rescue FMT for AAD in critically ill patients. Methods A series of critically ill patients with AAD received rescue FMT from Chinese fmtBank, from September 2015 to February 2019. Adverse events (AEs) and rescue FMT success which focused on the improvement of abdominal symptoms and post-ICU survival rate during a minimum of 12 weeks follow-up were assessed. Results Twenty critically ill patients with AAD underwent rescue FMT, and 18 of them were included for analysis. The mean of Acute Physiology and Chronic Health Evaluation (APACHE) II scores at intensive care unit (ICU) admission was 21.7 ± 8.3 (range 11–37). Thirteen patients received FMT through nasojejunal tube, four through gastroscopy, and one through enema. Patients were treated with four (4.2 ± 2.1, range 2–9) types of antibiotics before and during the onset of AAD. 38.9% (7/18) of patients had FMT-related AEs during follow-up, including increased diarrhea frequency, abdominal pain, increased serum amylase, and fever. Eight deaths unrelated to FMT occurred during follow-up. One hundred percent (2/2) of abdominal pain, 86.7% (13/15) of diarrhea, 69.2% (9/13) of abdominal distention, and 50% (1/2) of hematochezia were improved after FMT. 44.4% (8/18) of patients recovered from abdominal symptoms without recurrence and survived for a minimum of 12 weeks after being discharged from ICU. Conclusion In this case series studying the use of FMT in critically ill patients with AAD, good clinical outcomes without infectious complications were observed. These findings could potentially encourage researchers to set up new clinical trials that will provide more insight into the potential benefit and safety of the procedure in the ICU. Trial registration ClinicalTrials.gov, Number NCT03895593. Registered 29 March 2019 (retrospectively registered).

In recent years, the utilization of unmanned aerial vehicles (UAVs) for aerial target detection has gained significant attention due to their high-altitude perspective and maneuverability, which offer novel opportunities and tremendous potential in this field. However, detecting targets in UAV aerial images remains highly challenging due to the presence of numerous small targets with limited feature information, as well as issues like target occlusion and complex backgrounds that severely impact detection accuracy. To address these challenges, we propose a detection model called BDC-YOLOv8 that aims to enhance accuracy for small targets while minimizing computational complexity. Specifically, we augment the YOLOv8 architecture by incorporating a dedicated detection head tailored for small targets to improve performance when encountering such objects. Additionally, we restructure the neck network of the model to better extract and fuse feature information from targets with significant scale variations. Furthermore, we introduce the concept of DynamicHead to enhance the detection head by incorporating various attention mechanisms suitable for our task ahead of the original detection head, thereby enhancing the model's capability to detect objects of different scales and complex backgrounds. Moreover, we introduce Convolutional Block Attention Module (CBAM) to identify regions of interest in densely populated areas. Extensive experiments conducted on the VisDrone2019 dataset yield promising results where our model achieves a mean Average Precision (mAP) score of 38% and an AP50 score of 59.6%. Compared to the original YOLOV8 model, improvements are observed with increases in mAP by 2.5% and AP50 by 3.7%, respectively. Notably, our model demonstrates a significant enhancement in detecting small targets with an increase in APs evaluation metric by 4.1%. [ABSTRACT FROM AUTHOR]