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Abstract Background Sepsis-induced cardiomyopathy (SICM) is a common and life-threatening complication of sepsis, significantly contributing to elevated mortality. This study aimed to identify crucial indicators for the prompt and early assessment of SICM. Methods Patients diagnosed with sepsis or SICM within 24 h of intensive care unit (ICU) admission were enrolled in this prospective observational study. Patients were assigned to the training set, validation set and external test set. The primary endpoint was 7-day ICU mortality, and the secondary endpoint was 28-day ICU mortality. Three machine learning algorithms were utilized to identify relevant indicators for diagnosing SICM, incorporating 64 indicators including serum biomarkers associated with cardiac, renal, and liver function, lipid metabolism, coagulation, and inflammation. Internal and external validations were performed on the screening results. Patients were then stratified based on the cut-off value of the most diagnostically effective biomarker identified, and their prognostic outcomes were observed and analyzed. Results A total of 270 patients were included in the training and validation set, and 52 patients were included in the external test set. Age, sex, and comorbidities did not significantly differ between the sepsis and SICM groups (P > 0.05). The support vector machine (SVM) algorithm identified six indicators with an accuracy of 84.5%, the random forest (RF) algorithm identified six indicators with an accuracy of 81.9%, and the logistic regression (LR) algorithm screened out seven indicators. Following rigorous selection, a diagnostic model for sepsis-induced cardiomyopathy was established based on heart-type fatty acid binding protein (H-FABP) (OR 1.308, 95% CI 1.170–1.462, P

Abstract BackgroundSarcopenia is characterized by the loss of skeletal muscle mass and muscle function with increasing age. The skeletal muscle mass of older people who endure sarcopenia may be improved via the practice of strength training and tai chi. However, it remains unclear if the hybridization of strength exercise training and traditional Chinese exercise will have a better effect. ObjectiveWe designed a strength training and tai chi exercise hybrid program to improve sarcopenia in older people. Moreover, explainable artificial intelligence was used to predict postintervention sarcopenic status and quantify the feature contribution. MethodsTo assess the influence of sarcopenia in the older people group, 93 participated as experimental participants in a 24-week randomized controlled trial and were randomized into 3 intervention groups, namely the tai chi exercise and strength training hybrid group (TCSG; n=33), the strength training group (STG; n=30), and the control group (n=30). Abdominal computed tomography was used to evaluate the skeletal muscle mass at the third lumbar (L3) vertebra. Analysis of demographic characteristics of participants at baseline used 1-way ANOVA and χ2 ResultsA significant interaction effect was found in skeletal muscle density at the L3 vertebra, skeletal muscle area at the L3 vertebra (L3 SMA), grip strength, muscle fat infiltration, and relative skeletal muscle mass index (all PPF1 ConclusionsThe skeletal muscle area of older adults with sarcopenia may be improved by a hybrid exercise program composed of strength training and tai chi. In addition, we identified that the LightGBM classification model had the best performance to predict the reversion of sarcopenia.

BackgroundOver the past 2 years, researchers have used various medical licensing examinations to test whether ChatGPT (OpenAI) possesses accurate medical knowledge. The performance of each version of ChatGPT on the medical licensing examination in multiple environments showed remarkable differences. At this stage, there is still a lack of a comprehensive understanding of the variability in ChatGPT’s performance on different medical licensing examinations. ObjectiveIn this study, we reviewed all studies on ChatGPT performance in medical licensing examinations up to March 2024. This review aims to contribute to the evolving discourse on artificial intelligence (AI) in medical education by providing a comprehensive analysis of the performance of ChatGPT in various environments. The insights gained from this systematic review will guide educators, policymakers, and technical experts to effectively and judiciously use AI in medical education. MethodsWe searched the literature published between January 1, 2022, and March 29, 2024, by searching query strings in Web of Science, PubMed, and Scopus. Two authors screened the literature according to the inclusion and exclusion criteria, extracted data, and independently assessed the quality of the literature concerning Quality Assessment of Diagnostic Accuracy Studies-2. We conducted both qualitative and quantitative analyses. ResultsA total of 45 studies on the performance of different versions of ChatGPT in medical licensing examinations were included in this study. GPT-4 achieved an overall accuracy rate of 81% (95% CI 78-84; P

Enlarging the lateral space of drip tubes saves irrigation equipment costs (drip tubes and bypass), but it will lead to an increased risk of grain yield heterogeneity between wheat rows. Adjusting wheat row spacing is an effective cultivation measure to regulate a row’s yield heterogeneity. During a 2-year field experiment, we investigated the variations in yield traits and photosynthetic physiology by utilizing two different water- and fertilizer-demanding spring wheat cultivars (NS22 and NS44) under four kinds of drip irrigation patterns with different drip tube lateral spacing and wheat row spacing [① TR4, drip tube spacing (DTS) was 60 cm, wheat row horizontal spacing (WRHS) was 15 cm; ② TR6, DTS was 90 cm, WRHS was 15 cm; ③ TR6L, DTS was 90 cm, WRHS was 10 cm, inter-block spacing (IBS) was 35 cm; and ④ TR6S, DTS was 80 cm, WRHS was 10 cm, IBS was 25 cm]. The results showed that under 15-cm equal row spacing condition, after the number of wheat rows served by a single tube increased from four (TR4, control) to six (TR6), NS22 and NS44 exhibited a marked decline in yield. The decline of NS22 (9.93%) was higher than that of NS44 (9.04%), and both cultivars also showed a greater decrease in grain weight and average grain-filling rate (AGFR) of inferior grains (NS22: 23.19%, 13.97%; NS44: 7.78%, 5.86%) than the superior grains (NS22: 10.60%, 8.33%; NS44: 4.89%, 4.62%). After the TR6 was processed to narrow WRHS (from 15 to 10 cm) and add IBS (TR6L: 35 cm; TR6S: 25 cm), the grain weight per panicle (GWP) and AGFR of superior and inferior grains in the third wheat row (RW3) of NS22 and NS44 under TR6L increased significantly by 26.05%, 8.22%, 14.05%, 10.50%, 5.09%, and 5.01%, respectively, and under TR6S, they significantly increased by 20.78%, 9.91%, 16.19%, 9.28%, 5.01%, and 4.14%, respectively. The increase in GWP and AGFR was related to the increase in flag leaf area, net photosynthetic rate, chlorophyll content, relative water content, actual photochemical efficiency of PSII, and photochemical quenching coefficient. Among TR4, TR6, TR6L, and TR6S, for both NS22 and NS44, the yield of TR6S was significantly higher than that of TR6 and TR6L. Furthermore, TR6S showed the highest economic benefit.

The image-recipe cross-modal retrieval task, which retrieves the relevant recipes according to food images and vice versa, is now attracting widespread attention. There are two main challenges for image-recipe cross-modal retrieval task. Firstly, a recipe’s different components (words in a sentence, sentences in an entity, and entities in a recipe) have different weight values. If a recipe’s different components own the same weight, the recipe embeddings cannot pay more attention to the important components. As a result, the important components make less contribution to the retrieval task. Secondly, the food images have obvious properties of locality and only the local food regions matter. There are still difficulties in enhancing the discriminative local region features in the food images. To address these two problems, we propose a novel framework named Dual Cross Attention Encoders for Cross-modal Food Retrieval (DCA-Food). The proposed framework consists of a hierarchical cross attention recipe encoder (HCARE) and a cross attention image encoder (CAIE). HCARE consists of three types of cross attention modules to capture the important words in a sentence, the important sentences in an entity and the important entities in a recipe, respectively. CAIE extracts global and local region features. Then, it calculates cross attention between them to enhance the discriminative local features in the food images. We conduct the ablation studies to validate our design choices. Our proposed approach outperforms the existing approaches by a large margin on the Recipe1M dataset. Specifically, we improve the R@1 performance by +2.7 and +1.9 on the 1k and 10k testing sets, respectively.

IntroductionIn November 2022, the online artificial intelligence (AI) chatbot ChatGPT was released to the public, and swiftly garnered global attention because of its ability to provide detailed answers to complex queries. In medical field, ChatGPT has shown great potential to be used in medical education and has excelled in many English-language medical licensing examinations. However, due to the variability of medical licensing examinations in different countries, and ChatGPT's particular proficiency in English, the previous literatures showed that ChatGPT is unable to pass medical licensing examinations from non-English-speaking countries or those not administered in English. To the best of our knowledge, this is the first study to review whether ChatGPT can demonstrate consistent accuracy across diverse medical licensing examinations and be used in medical education across countries.ObjectiveIn this study protocol, we aimed to analyze and review the differences in performance of ChatGPT in medical exams in various language environments and countries, as well as its potential in medical education.Methods and analysisA systematic review and meta-analysis was conducted using PubMed, Web of Science, and Scopus to collect papers testing the performance of ChatGPT in medical licensing examinations. We imported all the collected literatures into Rayyan and screened the literatures based on the selection criteria and exclusion criteria. The risk of bias and quality of included studies was assessed by using Mixed Methods Appraisal Tool (MMAT). Data from included studies was extracted into an Excel spreadsheet. All of the above processes were completed by two reviewers independently. A third reviewer was consulted in cases of disagreement. Finally, we provided both quantitative and qualitative analysis of the findings from the included studies.Trial registrationPROSPERO registration number: CRD42024506687.

A sensitive and simple method for detecting Cu2+ in the water source was proposed by using surface-enhanced Raman scattering spectroscopy (SERS) based on the Ag@SiO2/Au core–shell composite. The Ag@SiO2 SERS tag was synthesized by a simple approach, in which Ag nanoparticles were first embedded with Raman reporter PATP and next coated with a SiO2 shell. The Ag@SiO2 nanoparticles had strong stability even in a high-concentration salty solution, and there were no changes to their properties and appearance within one month. The Ag@SiO2/Au composite was fabricated through a controllable self-assemble process. L-cysteine was decorated on the surface of a functionalized Ag@SiO2/Au composite, as the amino and carboxyl groups of it can form coordinate covalent bond with Cu2+, which shows that the Ag@SiO2/Au composite labelled with L-cysteine has excellent performance for the detection of Cu2+ in aqueous media. In this study, the SERS detection of Cu2+ was carried out using Ag@SiO2 nanoparticles, and the limit of detection (LOD) as low as 0.1 mg/L was achieved.

A suitable population structure is the foundation for a high yield of wheat. Studying the changes in yield and population structure of different wheat rows under drip irrigation conditions can provide a theoretical basis for optimizing wheat drip irrigation pattern. In a two-year field experiment, two different water- and fertilizer-demanding spring wheat varieties (XC22 and XC44) were used to study the changes of stem and tiller dynamics, dry matter accumulation, canopy photo-synthetically active radiation (PAR) interception, and canopy apparent photosynthesis rate (CAP) under one tube serving four rows of wheat drip irrigation pattern (TR4, drip lateral spacing (DLS) = 60 cm, wheat row spacing (WRS) = 15 cm) and one tube serving six rows of wheat drip irrigation pattern (TR6, DLS = 90 cm, WRS = 15 cm; TR6L, DLS = 90 cm, WRS = 10 cm and TR6S, DLS = 80 cm, WRS = 10 cm). The results showed that under the condition of equal row spacing of 15 cm, after increasing the number of wheat rows serving by one drip irrigation tube from four (TR4, control) to six (TR6), the yields (water use efficiency) of XC22 and XC44 were lower by 11.19% and 8.63%, respectively. The reduction of yield was related to uneven population growth, specifically as follows: compared with the first wheat row (R1), at flowering stage the leaf area index (LAI) and PAR interception in the third wheat row (R3) of XC22 and XC44 were significantly decreased by 30.02%, 18.69%, 9.59%, and 14.74%, respectively. At the maturity stage, the biomass, plant height, and panicles number of tiller (TPN) in R3 were significantly decreased by 22.15%, 12.34%, 15.46%, 5.24%, 65.07%, and 42.11%, respectively. At the jointing, flowering, and milk-ripening stage, the CAP were significantly decreased by 24.65%, 22.85%, 17.06%, 14.02%, 42.14%, and 32.27%, respectively, the decrease of XC22 were all higher than that of XC44 (except for PAR interception). After the TR6 pattern was processed to narrow the wheat row spacing from 15 cm to 10 cm under the condition of the same drip tube lateral spacing (TR6L) and under the condition of shortening drip tube lateral spacing by 10 cm (TR6S), the yields in R3 of XC22 and XC44 were significantly increased by 20.07%, 18.43%, 30.39%, and 23.80%, respectively, and the increase in yields were related to the improvement of LAI, biomass, plant height, TPN, PAR interception, and increased population photosynthesis. Among the four drip irrigation patterns, for both XC22 and XC44, the yield of TR6S was the closest to that of TR4, and the yields of them were significantly higher than that of TR6 and TR6L.

Objectives This study aimed to explore the predictive value of single and multiple risk factors for the clinical outcomes of critically ill patients receiving enteral nutrition and to establish an effective evaluation model.Design Retrospective cohort study.Setting Data from the 2020–2021 period were collected from the electronic records of the First Affiliated Hospital, Nanjing Medical University.Participants 459 critically ill patients with enteral nutrition in the geriatric intensive care unit were included in the study.Primary and secondary outcome measures The primary outcome was 28-day mortality. The secondary outcomes were 28-day invasive mechanical ventilation time, intensive care unit stay, Nutrition Risk Screening 2002 (NRS2002) score and Acute Physiology and Chronic Health Evaluation II (APACHE II) score.Results Independent prognostic factors, including prealbumin/procalcitonin (PCT) ratio and APACHE II score, were identified using a logistic regression model and used in the nomogram. The area under the receiver operating characteristic curve and concordance index indicated that the predictive capacity of the model was 0.753. Moreover, both the prealbumin/PCT ratio and the combination model of PCT, prealbumin and NRS2002 had a higher predictive value for clinical outcomes. Subgroup analysis also identified that a higher inflammatory state (PCT >0.5 ng/mL) and major nutritional risk (NRS2002 >3) led to worse clinical outcomes. In addition, patients on whole protein formulae bore less nutritional risk than those on short peptide formulae.Conclusions This nomogram had a good predictive value for 28-day mortality in critically ill patients receiving enteral nutrition. Both the prealbumin/PCT ratio and the combination model (PCT, prealbumin and NRS2002), as composite models of inflammation and nutrition, could better predict the prognosis of critically ill patients.

Wild jujube (Ziziphus acidojujuba) and cultivated jujube (Ziziphus jujuba) belong to the family Rhamnaceae. Jujubes have marked drought- and salt-tolerant properties. After salt stress, wild jujube seedling growth was inhibited and photosynthetic efficiency was reduced. A bioinformatics approach was used to analyze the transcriptomics data from wild jujube seedlings grown under salt stress, and the genes differentially expressed under the salt stress were identified to provide a theoretical basis for the development and use of wild jujube plantations in salinized soil. The transcriptome sequencing from leaves of wild jujube seedlings was carried out using second-generation sequencing technology. The effects of salt stress on the differential expression of photosynthesis-related genes in wild jujube seedlings were analyzed. Transcriptome sequencing revealed a total of 5269 differentially expressed genes (DEGs), of which 2729 were up-regulated and 2540 were down-regulated. DEGs were mainly enriched with respect to photosynthesis, photosynthetic antenna proteins, glyoxylic acid and dicarboxylic acid metabolism, linolenic acid metabolism, cysteine and methionine metabolism, and porphyrin and chlorophyll metabolism. Among them, the photosynthesis pathway-related DEGs were most highly enriched. Further analysis of porphyrin and chlorophyll synthesis and photosynthesis-related pathways revealed that they were significantly enriched by 97 photosynthesis-related DEGs. The DEGs in the photosynthesis and photosynthetic antenna protein pathways were down-regulated, whereas the DEGs glutamyl-tRNA reductase (HEMA), ferrochelatase (HEMH), and pheophorbide a oxygenase (PAO) in the porphyrin and chlorophyll synthesis pathways were up-regulated, with the remainder being down-regulated. The nuclear gene encoding Rubisco, the key enzyme in the photosynthetic carbon fixation pathway, was also down-regulated. The results showed that the photosynthetic rate of wild jujube seedlings decreased following exposure to salinity stress, an effect that was related to the increased synthesis of 5-aminolevulinic acid and heme, and the up-regulation of expression of a gene encoding a chlorophyll-degrading enzyme, and was related to the down-regulation of gene expression in photosynthesis-related pathways such as light energy capture and carbon fixation. Selection of nine DEGs related to photosynthesis and chlorophyll biosynthesis by quantitative real-time-PCR confirmed that expression changes of these nine DEGs were consistent with the transcriptome sequencing results.

As one of the most widely cultivated cotton species in China, upland cotton has moderate fiber quality and wide applicability, but its genetic basis is relatively narrow. To expand genetic diversity and improve fiber quality, in this study an introgression population (BC5S5) containing 107 lines was constructed by using G. hirsutum acc. 4105 as the recurrent parent and G. tomentosum as the donor parent. Using the specific-locus amplified fragment sequencing (SLAF-seq) strategy, 3157 high-throughput single nucleotide polymorphism (SNP) markers were obtained. Linkage analysis showed that a total of ninety-one QTLs related to fiber quality traits were detected in three environments, and the phenotypic variance explained (PVE) rates were 4.53–20.92%. Forty-six QTL (50.55%) synergistic genes were derived from G. tomentosum. Among them, qFS-A02-1 and qSCI-A02-1 were stably detected with a PVE of 9.8–16.71% and 14.78–20.92%, respectively. Within the candidate interval, Ghir_A02G012730, Ghir_A02G012790 and Ghir_A02G012830 were found to be possibly involved in cellulose and cell wall biosynthesis, with a relatively high expression during fiber development, 20 DPA and 25 DPA, which suggested that these three genes may be involved in the regulation of fiber strength traits, but their functions need further validation to determine the regulatory mechanism. Our research lays the foundation of fiber quality related to basic genetic research and breeding in cotton.

With the promotion and popularization of machine cotton-picking, more and more attention has been paid to the selection of early-maturity varieties with compact plant architecture. The type of fruit branch is one of the most important factors affecting plant architecture and early maturity of cotton. Heredity analysis of the cotton fruit branch is beneficial to the breeding of machine-picked cotton. Phenotype analysis showed that the types of fruit branches in cotton are controlled by a single recessive gene. Using an F2 population crossed with Huaxin102 (normal branch) and 04N-11 (nulliplex branch), BSA (Bulked Segregant Analysis) resequencing analysis and GhNB gene cloning in 04N-11, and allelic testing, showed that fruit branch type was controlled by the GhNB gene, located on chromosome D07. Ghnb5, a new recessive genotype of GhNB, was found in 04N-11. Through candidate gene association analysis, SNP 20_15811516_SNV was found to be associated with plant architecture and early maturity in the Xinjiang natural population. The GhNB gene, which is related to early maturity and the plant architecture of cotton, is a branch-type gene of cotton. The 20_15811516_SNV marker, obtained from the Xinjiang natural population, was used for the assisted breeding of machine-picked cotton varieties.

In view of the fact that the fast-neutron experimental cross-section data of hafnium which is an important structural material of fusion reactor are few and there are the great differences in their evaluation values, several activation cross sections of (n, 2n), (n, p), (n, a) and (n, n′) reactions on hafnium isotopes have been investigated by neutrons generated from the T(d, n) ^4 He reaction at the K-400 Neutron Generator at China Academy of Engineering Physics (CAEP). The gamma activities of the product nuclei were measured by a high-resolution gamma-ray spectrometer with a coaxial high-purity germanium detector. The ^93 Nb(n, 2n) ^92m Nb reaction was used as neutron fluence standard, these experimental cross sections of the ^174 Hf(n, 2n) ^173 Hf, ^176 Hf(n, 2n) ^175 Hf, ^178 Hf(n, α ) ^175m+g Yb, ^178 Hf(n, p) ^178g Lu, ^178 Hf(n, p) ^178m Lu, ^180 Hf(n, 2n) ^179m2 Hf, ^180 Hf(n, α ) ^177m+g Yb and ^180 Hf(n, n′) ^180m Hf reactions were obtained in the neutron energy range of 13.5–14.8 MeV. These measured cross sections were discussed and compared with some previous experimental results from the literature and with the evaluation data from ENDF/B-VIII.0, CENDL-3.1, JEFF-3.3 and the theoretical results by using the computer code system Talys-1.9.