In-situ confining selenium within bubble - like carbon nanoshells for ultra-stable Li-Se batteries.

Lithium-selenium (Li-Se) batteries are promising energy storage devices. However, the long-term durability and high-rate performance of the Se cathode have been limited by significant volume expansion and the troublesome shuttle effect of polyselenides during repeated charging/discharging processes. To revolutionize these issues, we applied a top-down strategy through the in-situ trapping of amorphous Se within bubble-like carbon (BLC) frameworks, which can radically minimize the presence of surface-absorbed Se while enhancing Se loading capacity. This ingenious technique successfully encapsulates all Se species within carbon nanoshells, creating a distinct half-filled core-shell structure known as Se@void@BLC. This in-situ trapping approach ensures the efficient management of Se volume changes during repeated discharge and charge cycles. Moreover, an extraordinary Se loading capacity of up to 65.6 wt% is reached. Using the Se@void@BLC as cathode for Li-Se battery, we achieve a high initial Columbic efficiency of 84.2 %, a high reversible capacity of 585 mAh g-1, and an ultralow capacity decay of only 0.0037 % per cycle during 4000 cycles at 10 A g-1.

Molecularly imprinted dispersive micro solid-phase extraction and tandem derivatization for the determination of histamine in fermented wines.

Histamine causes allergic reactions and can serve as an indicator for assessing food quality. This study designed and developed a dispersive micro solid-phase extraction (D-µSPE) method that combined the advantages of dispersive liquid-liquid extraction and solid-phase extraction (SPE). Molecularly imprinted polymers (MIPs) were employed as the solid phase in the D-µSPE method to extract histamine in wine samples. We used microwave energy to significantly reduce the synthesis time, achieving an 11.1-fold shorter synthesis time compared to the conventional MIP synthetic method. Under optimized D-µSPE conditions, our results showed that the dispersive solvent could effectively increase the adsorption performance of MIPs in wine samples by 97.7%. To improve the sensitivity of histamine detection in gas chromatography-mass spectrometry, we employed the microwave-assisted tandem derivatization method to reuse excess derivatization reagents and reduce energy consumption and reaction time. Calibration curves were constructed for wine samples spiked with 0-400 nmol histamine using the standard addition method, resulting in good linearity with a coefficient of determination of 0.999. The intra- and inter-batch relative standard deviations of the slope and intercept were < 0.7% and < 5.3%, respectively. The limits of quantitation and detection were 0.4 nmol and 0.1 nmol, respectively. The developed method was successfully applied to analyze the histamine concentration in 10 commercial wine samples. In addition, the AGREEprep tool was used to evaluate the greenness performance of the developed method, which obtained a higher score than the other reported methods.

Gelatin-Based Hydrogel for Three-Dimensional Neuron Culture Application.

Gelatin is a biocompatible biomaterial composed of a variety of amino acids that provides a possibility to regulate the interaction between cationic amino acids and neural cells. Based on our first finding that the neuron viability was improved as the lysine on the gelatin was converted into a guanidine structure, a three-dimensional (3D) gelatin hydrogel composed of gelatin and poly(allylguanidine) (PAG) was prepared to investigate neural cell behaviors. As expected, improved neuron viability, neurite outgrowth, synaptogenesis, and inhibited glial cell growth were simultaneously observed in the gelatin cross-linked with the PAG hydrogel (G-PAG) but not in the gelatin hydrogel cross-linked with poly-d-lysine (PDL) or polyethylenimine (PEI). In addition, in vivo tests also illustrated that G-PAG could provide an environment for neural culture, with improving neuron viability and neurite outgrowth. Several hydrogel characteristics-including the swelling ratio, mechanical strength, and electric property-that theoretically can influence neural cell response showed no significant difference among them. Therefore, the guanidine structure of PAG was proposed to determine the behaviors of neural cells within the gelatin-polycation hydrogels, and we proposed that the neural cell behavior is regulated by a specific gelatin-neuron relationship. The information found in this study provides a concept to design and modify gelatin-based hydrogels for neural tissue engineering applications.

Inverted U-shaped association between bacillary dysentery and temperature: A new finding using a novel two-stage strategy in multi-region studies.

BACKGROUND: Bacillary dysentery (BD) has brought a significant public health concern in China. Temperature is one of the main factors affecting BD incidence. Due to the largely different temperature ranges between regions, the classic multi-region time series studies could only explore the relative temperature-BD association and showed that BD incidence is positively associated with relative temperature (i.e., temperature percentile), which does not conform to the laboratory knowledge that both high and low temperature interfere with the survival of bacteria. The association on relative temperature scale also limits the intuition of epidemiological meanings. METHODS: A novel two-stage strategy was proposed to investigate the association between monthly temperature and BD incidence on the original temperature scale in 31 provinces, China. In the first stage, truncated polynomial splines, as the substitute of the common natural splines or B-splines in generalized additive models, were used to characterize the temperature-BD association on the original temperature scale in each province. In the second stage, a multivariate meta-analysis compatible with missing values was used to pool the associations. The classic strategy based on relative temperature was used as a reference. RESULTS: The average temperature-BD association presented a U-inverted shape, but not a monotonically increasing shape obtained using the classic strategy. This inverted U-shaped association conforms more to the laboratory knowledge and the original-scale association also provided an intuitive perspective and an easily explanatory result. Another advantage is that the novel strategy can extrapolate the province-specific association outside the observed temperature ranges by utilizing information from other provinces, which is meaningful considering the frequent incidences of extreme temperatures. CONCLUSIONS: The association between temperature and BD incidence presented a U-inverted shape. The proposed strategy can efficiently characterize the association between exposure and outcome on original scale in a multi-region study with largely different exposure ranges.

Gut microbiome-derived ammonia modulates stress vulnerability in the host.

Ammonia has been long recognized as a metabolic waste product with well-known neurotoxic effects. However, little is known about the beneficial function of endogenous ammonia. Here, we show that gut ammonia links microbe nitrogen metabolism to host stress vulnerability by maintaining brain glutamine availability in male mice. Chronic stress decreases blood ammonia levels by altering gut urease-positive microbiota. A representative urease-producing strain, Streptococcus thermophilus, can reverse depression-like behaviours induced by gut microbiota that was altered by stress, whereas pharmacological inhibition of gut ammonia production increases stress vulnerability. Notably, abnormally low blood ammonia levels limit the brain's availability of glutamine, a key metabolite produced by astrocytes that is required for presynaptic γ-aminobutyric acid (GABA) replenishment and confers stress vulnerability through cortical GABAergic dysfunction. Of therapeutic interest, ammonium chloride (NH4Cl), a commonly used expectorant in the clinic, can rescue behavioural abnormalities and GABAergic deficits in mouse models of depression. In sum, ammonia produced by the gut microbiome can help buffer stress in the host, providing a gut-brain signalling basis for emotional behaviour.

[Challenges of Globalization and English as a Medium of Instruction in Nursing Teaching and Learning].

Higher education is becoming increasingly internationalized, and English as a medium of instruction (EMI) for academic content has become commonplace in countries where English is not a native language. However, concerns are growing that the fast-growing trend of EMI lacks sufficient consideration of the related challenges with regard to implementation and impact. As a complex phenomenon, EMI requires increased awareness of its positive and negative implications for teachers and students. The attitudes and perspectives of teachers and students play a significant role in influencing the promotion and effectiveness of EMI teaching. Nevertheless, internationalization is essential for the advancement of nursing education. Therefore, it is imperative to understand the perspectives and challenges faced by teachers and students with regard to EMI and their readiness to embrace it. Therefore, in this article, we first define EMI and describe the reasons for its introduction and then discuss the challenges that teachers and students involved with EMI face in order to provide a reference for nursing education policymakers and academic institutions tasked with EMI development and implementation.

Self-sacrificed BiOBr template-assisted synthesis of α-Bi2O3/Bi3O4Br heterojunctions with oxygen vacancies for enhanced photocatalytic nitrogen fixation.

The catalytic conversion of nitrogen to ammonia is one of the most significant processes in nature and the chemical industry. However, the traditional Haber-Bosch process of ammonia synthesis consumes substantial energy and emits a large amount of carbon dioxide. The efficiency of photocatalytic N2 activation is severely limited by the lack of N2 adsorption sites and poor carrier utilization. Herein, an efficient α-Bi2O3/Bi3O4Br heterojunction is proposed with a photocatalytic nitrogen fixation activity of 238.67 µmol·g-1·h-1. Compared with the BiOBr precursor, α-Bi2O3 and Bi3O4Br, the α-Bi2O3/Bi3O4Br heterojunction with oxygen vacancies can improve the adsorption and activation capacity of N2 and promote the separation efficiency of charge carrier pairs by accommodating photogenerated electrons under visible light through the mechanism of N-type semiconductors. Therefore, oxygen vacancies and heterojunction engineering of semiconductive nanomaterials provide a promising method for the rational design of photocatalysts to enhance the rate of ammonia synthesis under mild conditions.

Using a novel strategy to investigate the spatially autocorrelated and clustered associations between short-term exposure to PM2.5 and mortality and the attributable burden: A case study in the Sichuan Basin, China.

Due to the lack of statistical methods, few studies have investigated the spatial autocorrelated distribution in the association between short-term exposure to PM2.5 and mortality and used a statistical manner to explore the association-clustered regions, which play important roles in identifying high-sensitivity/susceptibility regions. The Sichuan Basin (SCB) is one of the most PM2.5-polluted areas, and the extreme economic imbalance may cause considerable spatial heterogeneity and clustering in PM2.5-mortality association. In this work, we used a recently proposed strategy by us to investigate the spatially autocorrelated and clustered association between daily PM2.5 and cardiorespiratory mortality from 2015 to 2019 in 130 counties of the SCB. First, generalized additive models were independently constructed to obtain the county-level association estimations. Then, an estimation-error-based spatial scan statistic was used to detect the association-clustered regions. Third, multivariate conditional meta autoregression was used to obtain the spatially autocorrelated association distribution, based on which the attributable deaths were mapped and their inequality was evaluated using the Gini coefficient and Lorenz curve. Results showed that two significantly association-clustered regions were detected. One is mainly located in the megacity Chengdu where PM2.5 presented a significantly stronger association with no threshold effect at low-level PM2.5 but a threshold at high-level PM2.5. In the other cluster, a threshold effect at low-level PM2.5 but no threshold at high-level PM2.5 were found. The mortality risk at low/middle-level PM2.5 decreased from Chengdu as the center to the surrounding areas. A total of 29,129 (2.0 %) deaths were attributable to the excess PM2.5 exposure. The attributable deaths also decreased from Chengdu as the center to the surrounding areas with Gini coefficients of 0.43 and 0.3 for absolute and relative attributable deaths, respectively. This novel strategy provided a new epidemiological perspective regarding the association and implicated that Chengdu is significantly deserving of more attention regarding PM2.5-related health loss.

Nanodiamonds-in-oil emulsions elicit potent immune responses for effective vaccination and therapeutics.

Background: The use of nanodiamonds (NDs) and fluorescent nanodiamonds (FNDs) as nonallergenic biocompatible additives in incomplete Freund's adjuvant (IFA) to elicit immune responses in vivo was investigated. Methods: C57BL/6 mice were immunized with chicken egg ovalbumin (OVA) in IFA and also OVA-conjugated NDs (or OVA-conjugated FNDs) in IFA to produce antibodies. OVA-expressing E.G7 lymphoma cells and OVA-negative EL4 cells were inoculated in mice to induce tumor formation. Results: The new formulation significantly enhanced immune responses and thus disease resistance. It exhibited specific therapeutic activities, effectively inhibiting the growth of E.G7 tumor cells in mice over 35 days. Conclusion: The high biocompatibility and multiple functionalities of NDs/FNDs render them applicable as active and trackable vaccine adjuvants and antitumor agents.

In situ assembly of nickel-based ultrathin catalyst film for water oxidation.

A nickel-based ultrathin catalyst film is assembled in situ from a solution of Ni(OAc)2 and a Schiff-base ligand L. The resulting ultrathin catalyst film shows a low overpotential of 330 mV, a steady current of 7 mA cm-2 for water oxidation over 10 h.

Facile Synthesis Hyper-Crosslinked PdFe Bimetallic Polymer as Highly Active Catalyst for Ullmann Coupling Reaction of Chlorobenzene.

The synthesis of efficient and sustainable heterogeneous Pd-based catalysts has been an active field of research due to their crucial role in carbon-carbon coupling reactions. In this study, we developed a facile and eco-friendly in situ assembly technique to produce a PdFe bimetallic hyper-crosslinked polymer (HCP@Pd/Fe) to use as a highly active and durable catalyst in the Ullmann reaction. The HCP@Pd/Fe catalyst exhibits a hierarchical pore structure, high specific surface area, and uniform distribution of active sites, which promote catalytic activity and stability. Under mild conditions, the HCP@Pd/Fe catalyst is capable of efficiently catalyzing the Ullmann reaction of aryl chlorides in aqueous media. The exceptional catalytic performance of HCP@Pd/Fe is attributed to its robust absorption capability, high dispersion, and strong interaction between Fe and Pd, as confirmed by various material characterizations and control experiments. Furthermore, the coated structure of a hyper-crosslinked polymer enables easy recycling and reuse of the catalyst for at least 10 cycles without any significant loss of activity.

Self-Powered DNAzyme Walker Enables Dual-Mode Biosensor Construction for Electrochemiluminescence and Electrochemical Detection of MicroRNA.

Herein, an electrochemiluminescence (ECL) and electrochemical (EC) dual-mode biosensor platform with a self-powered DNAzyme walking machine was established for accurate and sensitive detection of miRNA-21. By employing a magnesium ion (Mn2+)-dependent DNAzyme cleavage cycling reaction, the walking machine was built by assembling DNAzyme walking strands and ferrocene (Fc)-labeled substrate strands on the Au nanoparticles and graphitic carbon nitride nanosheet (g-C3N4 NS)-covered electrode. The DNAzyme walking strand was first prohibited by a blocker strand. After the addition of target miRNA-21 and Mn2+, the DNAzyme walker could be activated and produce autonomous movements along the electrode track fueled by Mn2+-dependent DNAzyme-catalyzed substrate cleavage without additional energy supply. Notably, each walking step resulted in the cleavage of a substrate strand and the release of a Fc-labeled DNA strand fragment, allowing us to acquire an extreme ECL signal recovery of g-C3N4 inhibited by Fc. Meanwhile, numerous Fc-labeled DNA fragments escaped from the surface of the electrode, directly producing an obvious decrease in the square wave voltammetry (SWV) signal from Fc on the same sensing platform. This work not only avoided difficultly assembling various signal indicators but also significantly improved the sensitivity through using self-powered DNAzyme-walker amplification. Moreover, the proposed design employed the same reaction to produce two signal output modes, which could eliminate the interference from diverse reactive pathways on the outcome to mutually improve the accuracy. Therefore, the dual-mode miRNA-21 biosensor exhibited wide detection ranges of 100 aM to 100 nM with low detection limits of 54.3 and 78.6 aM by ECL and SWV modes, respectively, which provided an efficient and universal biosensing approach with extensive applications in early disease diagnosis and bioanalysis.

Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States.

Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM2.5, O3, SO2, NO2, and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM2.5 and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO2 and SO2 were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner.

The Treatment Experience of Anorexia Nervosa in Adolescents from Healthcare Professionals' Perspective: A Qualitative Study.

Anorexia nervosa (AN) is a serious psychiatric illness with a high mortality rate and a poor outcome. AN in adolescents can be difficult to treat. The prognosis of patients with AN depends highly on how early specialized AN treatment starts. Therefore, the purpose of this study was to explore the experiences of healthcare professionals in treating adolescents with AN. A qualitative study approach was conducted. Through semi-structured interviews, 16 healthcare professionals, including 10 nurses, 3 dieticians and 3 physicians from the paediatric ward at a university-affiliated medical centre in central Taiwan, shared their experiences. Recorded interviews were transcribed and analyzed by content analysis. Five themes and ten subthemes were identified: 1. Building a trusting relationship first: (a) spending time to build trust with the client and (b) establishing a relationship with the client's parents; 2. The key to treatment success: (a) Clients' awareness of the illness and (b) parents' support for clients; 3. Consistency of team treatment goals: (a) maintaining stable vital signs and (b) achieving caloric intake; 4. Empowerment with knowledge about anorexia: (a) continuing education for healthcare professionals and (b) interdisciplinary collaborative care; and 5. Using different interaction strategies: (a) the hard approach and (b) the soft approach. In conclusion, the findings will provide important information for healthcare professionals to apply in monitoring the psychological and emotional states of adolescents with AN. The findings indicate that healthcare professionals should invite parents to participate in the treatment, support and guide them in their adolescent care, develop scales of family stress and support for AN in adolescents, develop interventions, and establish an early therapeutic alliance.

A deep learning-based model predicts survival for patients with laryngeal squamous cell carcinoma: a large population-based study.

OBJECTIVES: To assess the performance of DeepSurv, a deep learning-based model in the survival prediction of laryngeal squamous cell carcinoma (LSCC) using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: In this large population-based study, we developed and validated a deep learning survival neural network using pathologically diagnosed patients with LSCC from the SEER database between January 2010 and December 2018. Totally 13 variables were included in this network, including patients baseline characteristics, stage, grade, site, tumor extension and treatment details. Based on the total risk score derived from this algorithm, a three-knot restricted cubic spline was plotted to exhibit the difference of survival benefits from two treatment modalities. RESULTS: Totally 6316 patients with LSCC were included in the study, of which 4237 cases diagnosed between 2010 and 2015 were selected as the development cohort, and the rest (2079 cases diagnosed from 2016 to 2018) were the validation cohort. A state-of-the-art deep learning-based model based on 23 features (i.e., 13 variables) was generated, which showed more superior performance in the prediction of overall survival (OS) than the tumor, node, and metastasis (TNM) staging system (C-index for DeepSurv vs TNM staging = 0.71; 95% CI 0.69-0.74 vs 0.61; 95% CI 0.60-0.63). Interestingly, a significantly nonlinear association between total risk score and treatment effectiveness was observed. When the total risk score ranges 0.1-1.5, surgical treatment brought more survival benefits than nonsurgical one for LSCC patients, especially in 70.5% of patients staged III-IV. CONCLUSIONS: The deep learning-based model shows more potential benefits in survival estimation for patients with LSCC, which may potentially serve as an auxiliary approach to provide reliable treatment recommendations.

Epidemiological characteristics and risk factors of obstetric infection after the Universal Two-Child Policy in North China: a 5-year retrospective study based on 268,311 cases.

BACKGROUND: Obstetrical infection is one of the causes of maternal death and a difficult problem for many clinicians. Changes in the demographic and obstetric background of pregnant women following the Universal Two-Child Policy may have an impact on some fertility phenomena. And with the increase in the number of deliveries, the limited medical resources become more scarce. How will China's health system quickly adapt to the growing needs and expectations for maternal health and ensure the provision of qualified and accessible medical services? In addition, what social support measures should be provided to reduce preventable obstetric complications? Given the relatively low per capita share of medical resources in China, how should China deal with the impact of the Universal Two-Child Policy? Therefore, more studies based on the change of fertility policy are needed. We try to analyze the epidemiological characteristics and risk factors of obstetric infection before and after the Universal Two-Child Policy, with a view to providing reference for the prevention and control of obstetric infection in regions after the change of fertility policy, and also hope to make corresponding contributions to the solution of the above problems through relevant studies. METHODS: The subjects of the survey were 268,311 pregnant women from Hebei Province Maternal Near Miss Surveillance System (HBMNMSS) of Hebei Women and Children's Health Center from January 1, 2013 to December 31, 2017. We analyzed the region, time and population distribution characteristics of obstetric infection, compared the epidemiological factors of obstetric infection before and after the Universal Two-Child Policy, and analyzed the relevant risk factors of obstetric infection. RESULTS: The incidence of obstetric infection increased nearly twice after the Universal Two-Child Policy. The incidence of obstetric infection was highest in Chengde (1.9%), a city with a northward geographical distribution, Baoding (1.6%), Cangzhou (1.5%) followed; The higher the hospital grade, the higher the incidence; The incidence of obstetric infections in hospitals at all levels has increased; The age of onset before the Universal Two-Child Policy was (27.82 ± 5.047) years old, and the age after the Universal Two-Child Policy was (28.97 ± 4.880) years old; The incidence of obstetric infections is higher in winter. The rate of abortion-related infection (increased from 0.61 to 1.65%) and the rate of pregnant women with high school education (increased from 0.35 to 0.74%) increased significantly. The results of multivariate Logistic regression analysis after the Universal Two-Child Policy showed that anemia (OR = 1.249, 95%CI: 1.071-1.458), chronic hypertension (OR = 1.934, 95%CI: 1.375-2.722), mild preeclampsia (OR = 2.103, 95%CI: 1.323-3.344) and severe preeclampsia (OR = 2.228, 95%CI: 1.703-2.916) were independent risk factors for obstetric infection. Gestational age ≥ 37 weeks was a protective factor. CONCLUSION: After the Universal Two-Child Policy, the prevention and control of obstetric infections should be strengthened, especially for abortion-related infections and elderly maternal with obstetric complications and complication in high-grade hospitals in winter. Educational background is also one of the factors that should be considered in the prevention of obstetric sensation. Prolonging gestational age is helpful to reduce the incidence of obstetric infection.

Stratification of malignant renal neoplasms from cystic renal lesions using deep learning and radiomics features based on a stacking ensemble CT machine learning algorithm.

Using nephrographic phase CT images combined with pathology diagnosis, we aim to develop and validate a fusion feature-based stacking ensemble machine learning model to distinguish malignant renal neoplasms from cystic renal lesions (CRLs). This retrospective research includes 166 individuals with CRLs for model training and 47 individuals with CRLs in another institution for model testing. Histopathology results are adopted as diagnosis criterion. Nephrographic phase CT scans are selected to build the fusion feature-based machine learning algorithms. The pretrained 3D-ResNet50 CNN model and radiomics methods are selected to extract deep features and radiomics features, respectively. Fivefold cross-validated least absolute shrinkage and selection operator (LASSO) regression methods are adopted to identify the most discriminative candidate features in the development cohort. Intraclass correlation coefficients and interclass correlation coefficients are employed to evaluate feature's reproducibility. Pearson correlation coefficients for normal distribution features and Spearman's rank correlation coefficients for non-normal distribution features are used to eliminate redundant features. After that, stacking ensemble machine learning models are developed in the training cohort. The area under the receiver operator characteristic curve (ROC), calibration curve, and decision curve analysis (DCA) are adopted in the testing cohort to evaluate the performance of each model. The stacking ensemble machine learning algorithm reached excellent diagnostic performance in the testing dataset. The calibration plot shows good stability when using the stacking ensemble model. Net benefits presented by DCA are higher than the Bosniak 2019 version classification when employing any machine learning algorithm. The fusion feature-based machine learning algorithm accurately distinguishes malignant renal neoplasms from CRLs, which outperformed the Bosniak 2019 version classification, and proves to be more applicable for clinical decision-making.

Transdermal Delivery of Succinate Accelerates Energy Dissipation of Brown Adipocytes to Reduce Remote Fat Accumulation.

Weight loss by increasing energy consumption of thermogenic adipocytes to overcome obesity remains a challenge. Herein, we established a transdermal device that was based on the local and temporarily controlled delivery of succinate (SC), a tricarboxylic acid cycle metabolic intermediate to stimulate the thermogenesis pathway of uncoupling protein 1 (UCP1) and accelerate energy dissipation of brown adipose tissue (BAT) under the dorsal interscapular skin, further initiating the consumption of fatty acids by systemic metabolism. SC microneedle patches significantly suppressed weight gain and fat accumulation of remote organs, including liver and peripheral white adipose tissue (WAT) in high-fat diet-induced obese mice. mRNA expression levels of Ucp1 in BAT and other browning markers in WAT were significantly elevated in the mice that were treated with SC microneedle. Thus, the energy dissipation of BAT using UCP1-mediated thermogenesis accelerated by the transdermal delivery of SC may become a potential and effective strategy for preventing obesity.

Therapeutic experience of a pancreatic mixed serous neuroendocrine neoplasm invading peripancreatic vessels: A case report.

RATIONALE: Pancreatic mixed serous neuroendocrine neoplasm (PMSNN) is an extremely rare disease. Only a few cases on the surgical treatment of PMSNN have been reported in the literature, and it is unclear whether there is invasion of important peripancreatic vessels. PATIENT CONCERNS: We report the case of a 39-year-old female patient with PMSNN accompanied by invasion of important peripancreatic vessels. She underwent surgery and achieved satisfactory recovery. DIAGNOSIS: Abdominal enhanced CT images showed an enhanced mass with a nonenhanced cyst involving the head and body of the pancreas, which invaded important peripancreatic vessels. The lesion had been misdiagnosed and mistreated as a metastatic carcinoma before admission. INTERVENTIONS: CT 3-dimensional (3D) visualization reconstruction images showed intact peripancreatic vessels. Radical pancreatoduodenectomy was successfully performed and confirmed that the main blood vessels around the pancreas were only compressed or even wrapped by the mass, but not penetrated. OUTCOMES: The patient recovered well and was discharged on the 19th day after surgery. Pathological examination reported the diagnosis of PMSNN with the collision type combination and the well-differentiated grade 2 pancreatic neuroendocrine tumor. She was followed up for 18 months without any abnormalities. LESSONS: This case demonstrates that surgical treatment of PMSNN with invasion of peripancreatic vessels can be successful. Preoperative abdominal CT 3D visualization reconstruction is helpful in determining the degree of invasion of important peripancreatic vessels, and plays a key role in formulating an accurate surgical plan and improving patient outcome.

A machine learning model predicting candidates for surgical treatment modality in patients with distant metastatic esophageal adenocarcinoma: A propensity score-matched analysis.

Objective: To explore the role of surgical treatment modality on prognosis of metastatic esophageal adenocarcinoma (mEAC), as well as to construct a machine learning model to predict suitable candidates. Method: All mEAC patients pathologically diagnosed between January 2010 and December 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A 1:4 propensity score-matched analysis and a multivariate Cox analysis were performed to verify the prognostic value of surgical treatment modality. To identify suitable candidates, a machine learning model, classification and regression tree (CART), was constructed, and its predictive performance was evaluated by the area under receiver operating characteristic curve (AUC). Results: Of 4520 mEAC patients, 2901 (64.2%) were aged over 60 years and 4012 (88.8%) were males. There were 411 (9.1%) patients receiving surgical treatment modality. In the propensity score-matched analysis, surgical treatment modality was significantly associated with a decreased risk of death (HR: 0.47, 95% CI: 0.40-0.55); surgical patients had almost twice as much median survival time (MST) as those without resection (MST with 95% CI: 23 [17-27] months vs. 11 [11-12] months, P <0.0001). The similar association was also observed in the multivariate Cox analysis (HR: 0.47, 95% CI: 0.41-0.53). Then, a CART was constructed to identify suitable candidates for surgical treatment modality, with a relatively good discrimination ability (AUC with 95% CI: 0.710 [0.648-0.771]). Conclusion: Surgical treatment modality may be a promising strategy to prolong survival of mEAC patients. The CART in our study could serve as a useful tool to predict suitable candidates for surgical treatment modality. Further creditable studies are warranted to confirm our findings.