The policies on the use of large language models in radiological journals are lacking: a meta-research study.

OBJECTIVE: To evaluate whether and how the radiological journals present their policies on the use of large language models (LLMs), and identify the journal characteristic variables that are associated with the presence. METHODS: In this meta-research study, we screened Journals from the Radiology, Nuclear Medicine and Medical Imaging Category, 2022 Journal Citation Reports, excluding journals in non-English languages and relevant documents unavailable. We assessed their LLM use policies: (1) whether the policy is present; (2) whether the policy for the authors, the reviewers, and the editors is present; and (3) whether the policy asks the author to report the usage of LLMs, the name of LLMs, the section that used LLMs, the role of LLMs, the verification of LLMs, and the potential influence of LLMs. The association between the presence of policies and journal characteristic variables was evaluated. RESULTS: The LLM use policies were presented in 43.9% (83/189) of journals, and those for the authors, the reviewers, and the editor were presented in 43.4% (82/189), 29.6% (56/189) and 25.9% (49/189) of journals, respectively. Many journals mentioned the aspects of the usage (43.4%, 82/189), the name (34.9%, 66/189), the verification (33.3%, 63/189), and the role (31.7%, 60/189) of LLMs, while the potential influence of LLMs (4.2%, 8/189), and the section that used LLMs (1.6%, 3/189) were seldomly touched. The publisher is related to the presence of LLM use policies (p < 0.001). CONCLUSION: The presence of LLM use policies is suboptimal in radiological journals. A reporting guideline is encouraged to facilitate reporting quality and transparency. CRITICAL RELEVANCE STATEMENT: It may facilitate the quality and transparency of the use of LLMs in scientific writing if a shared complete reporting guideline is developed by stakeholders and then endorsed by journals. KEY POINTS: The policies on LLM use in radiological journals are unexplored. Some of the radiological journals presented policies on LLM use. A shared complete reporting guideline for LLM use is desired.

[Spatial and Temporal Distribution of Antibiotic Resistance Genes in Different River Sediments in Typical Cities: A Case Study of Shijiazhuang].

Rivers are important reservoirs of antibiotic resistance genes (ARGs). However, most current studies have focused on the temporal and spatial distribution, and data on the differences in the species and abundance of ARGs between urban and rural rivers is still lacking for certain areas. In view of this, two rural rivers and three urban rivers were selected in Shijiazhuang City. In both December 2020 and April 2021, sediments were collected at 15 sampling sites. Metagenomic sequencing technology was used to compare the differences in temporal-spatial variation for ARGs in sediments. The results showed that:① 162 and 79 ARGs were detected in urban (4 776 ±4 452) and rural rivers (1 043 ±632), respectively. The abundance and species of ARGs in urban rivers were higher than those in rural rivers. ② The relative abundances of sulfonamide (SAs,27 %), aminoglycoside (AGs,26 %), and multidrug (MDs,15 %) ARGs had the highest abundance in urban rivers, whereas the relative abundance of MDs ARGs was highest in rural rivers (65 %). On the whole, the complexity of ARGs in urban rivers was higher than that in rural rivers. ③ There was a significant positive correlation between SAs, AGs, MDs, tetracycline, phenicol, macrolides-lincosamids-streptogramins (MLS), ß-lactams, and diaminopyrimidine ARGs in urban rivers (P < 0.01); however, there was a significant negative correlation between glycopeptide ARGs and all types of ARGs (P < 0.05 and P < 0.01). There was a significant positive correlation between MDs and SAs ARGs in rural rivers (P < 0.05), but there was a significant negative correlation between amino aminocoumarin, peptide, rifamycin, and fosfomycin ARGs (P < 0.05 and P < 0.01). ④ For the temporal variation in urban rivers, 162 ARGs (4 776 ±4 452) and 148 ARGs (5 673 ±5 626) were detected in December and April, respectively. For the temporal variation in rural rivers, 79 species (1 043 ±632) and 46 species (467 ±183) were detected in December and April, respectively. ⑤ RDA analysis results showed that the spatial-temporal distributions of ARGs in urban and rural rivers were different. Correlation analysis showed that the ARGs in urban rivers were significantly correlated with the number of industrial enterprises, whereas the ARGs in rural rivers were significantly correlated with the output value of animal husbandry. In general, this study identified the main influencing factors for ARGs in different rivers and provided data support for ARGs risk management in different rivers.

Trophic transfer of antibiotics in the benthic-pelagic coupling foodweb in a macrophyte-dominated shallow lake: The importance of pelagic-benthic coupling strength and baseline organism.

In lake ecosystems, pelagic-benthic coupling strength (PBCS) is closely related to foodweb structure and pollutant transport. However, the trophic transfer of antibiotics in a benthic-pelagic coupling foodweb (BPCFW) and the manner in which PBCS influences the trophic magnification factor (TMFs) of antibiotics is still not well understood in the whole lake. Herein, the trophic transfer behavior of 12 quinolone antibiotics (QNs) in the BPCFW of Baiyangdian Lake were studied during the period of 2018-2019. It was revealed that 24 dominant species were contained in the BPCFW, and the trophic level was 0.42-2.94. Seven QNs were detected in organisms, the detection frequencies of ofloxacin (OFL), flumequine (FLU), norfloxacin (NOR), and enrofloxacin (ENR) were higher than other QNs. The ∑QN concentration in all species was 11.3-321 ng/g dw. The TMFs for ENR and NOR were trophic magnification, while for FLU/OFL it was trophic dilution. The PBCS showed spatial-temporal variation, with a range of 0.6977-0.7910. The TMFs of ENR, FLU, and OFL were significantly positively correlated with PBCS. Phytoplankton and macrophyte biomasses showed indirect impact on the TMFs of QNs by directly influencing the PBCS. Therefore, the PBCS was the direct influencing factor for the TMFs of chemicals.

Characterization of Pancreatic Fistula after Post-pancreatectomy Acute Pancreatitis.

OBJECTIVE: This study aimed to investigate the clinical significance and risk factors of postoperative pancreatic fistula (POPF) after post-pancreatectomy acute pancreatitis (PPAP) in patients who underwent pancreaticoduodenectomy (PD). SUMMARY BACKGROUND DATA: PPAP has been recognized as a critical factor in the pathophysiology of POPF after PD. METHODS: A total of 817 consecutive patients who underwent elective PD between January 2020 and June 2022 were included. PPAP and POPF were defined in accordance with the International Study Group for Pancreatic Surgery (ISGPS) definitions. Multivariate logistic analyses were performed to investigate the risk factors for POPF. Comparisons between PPAP-associated POPF and non-PPAP-associated POPF were made to further characterize this intriguing complication. RESULTS: Overall, 159 (19.5%) patients developed POPF after PD, of which 73 (45.9%) occurred following PPAP, and the remaining 86 (54.1%) had non-PPAP-associated POPF. Patients with PPAP-associated POPF experienced significantly higher morbidity than patients without POPF. Multivariate analyses revealed distinct risk factors for each POPF type. For PPAP-associated POPF, independent risk factors included estimated blood loss >200 mL (OR 1.93), MPD ≤3 cm (OR 2.88), and soft pancreatic texture (OR 2.01), largely overlapping with FRS (Fistula Risk Score) elements. On the other hand, non-PPAP-associated POPF was associated with age >65 years (OR 1.95), male (OR 2.10), and MPD ≤3 cm (OR 2.57). Notably, among patients with PPAP, the incidence of POPF consistently hovered around 50% regardless of the FRS stratification. CONCLUSIONS: PPAP-associated POPF presents as a distinct pathophysiology in the development of POPF after PD, potentially opening doors for future prevention strategies targeting the early postoperative period.

Antibiotic resistance genes and mobile genetic elements in different rivers: The link with antibiotics, microbial communities, and human activities.

Rivers as a critical sink for antibiotic resistance genes (ARGs), and the distribution and spread of ARGs are related to environmental factors, human activities, and biotic factors (e.g. mobile genetic elements (MGEs)). However, the potential link among ARGs, microbial community, and MGEs in rivers under different antibiotic concentration and human activities remains unclear. In this study, 2 urban rivers (URs), 1 rural-urban river (RUR), and 2 rural rivers (RRs) were investigated to identify the spatial-temporal variation and driving force of ARGs. The total concentration of quinolones (QNs) was 160.1-2151 ng·g-1 in URs, 23.34-1188 ng·g-1 in RUR, and 16.39-85.98 ng·g-1 in RRs. Total population (TP), gross domestic production (GDP), sewage, industrial enterprise (IE), and IEGDP appeared significantly spatial difference in URs, RUR, and RRs. In terms of ARGs, 145-161 subtypes were detected in URs, 59-61 subtypes in RURs, and 46-79 subtypes in RRs. For MGEs, 55-60 MGEs subtypes were detected in URs, 29-30 subtypes in RUR, and 29-35 subtypes in RRs. Significantly positive correlation between MGEs and ARGs were found in these rivers. More ARGs subtypes were related to MGEs in URs than those in RUR and RRs. Overall, MGEs and QNs showed significantly direct positive impact on the abundance of ARGs in all rivers, while microbial community was significantly positive impact on the ARGs abundance in URs and RUR. The ARGs abundance in URs/RUR were directly positive influenced by microbial community/MGEs/socioeconomic elements (SEs)/QNs, while those in RRs were directly positive influenced by QNs/MGEs and indirectly positive impacted by SEs. Most QNs resistance risk showed significantly positive correlation with the abundance of ARGs types. Therefore, not only need to consider the concentration of antibiotics, but also should pay more attention to SEs and MGEs in antibiotics risk management and control.

The Effect of Perioperative Dexamethasone on Postoperative Complications After Pancreaticoduodenectomy: A Multicenter Randomized Controlled Trial.

OBJECTIVE: To evaluate the effect of perioperative dexamethasone on postoperative complications after pancreaticoduodenectomy. BACKGROUND: The glucocorticoid dexamethasone has been shown to improve postoperative outcomes in surgical patients, but its effects on postoperative complications after pancreaticoduodenectomy are unclear. METHODS: This multicenter, double-blind, randomized controlled trial was conducted in four Chinese high-volume pancreatic centers. Adults undergoing elective pancreaticoduodenectomy were randomized to receive either 0.2 mg/kg dexamethasone or a saline placebo as an intravenous bolus within 5 minutes after anesthesia induction. The primary outcome was the Comprehensive Complication Index (CCI) score within 30 days after the operation, analyzed using the modified intention-to-treat principle. RESULTS: Among 428 patients for eligibility, 300 participants were randomized and 265 were included in the modified intention-to-treat analyses. One hundred thirty-four patients received dexamethasone and 131 patients received a placebo. The mean (SD) CCI score was 14.0 (17.5) in the dexamethasone group and 17.9 (20.3) in the placebo group (mean difference: -3.8; 95% CI: -8.4 to 0.7; P = 0.100). The incidence of major complications (Clavien-Dindo grade ≥III; 12.7% vs 16.0%, risk ratio: 0.79; 95% CI: 0.44 to 1.43; P = 0.439) and postoperative pancreatic fistula (25.4% vs 31.3%, risk ratio: 0.81; 95% CI: 0.55 to 1.19; P = 0.286) were not significantly different between the two groups. In the stratum of participants with a main pancreatic duct ≤3 mm (n = 202), the CCI score was significantly lower in the dexamethasone group (mean difference: -6.4; 95% CI: -11.2 to -1.6; P = 0.009). CONCLUSIONS: Perioperative dexamethasone did not significantly reduce postoperative complications within 30 days after pancreaticoduodenectomy.