Search

Abstract Background In recent years, there has been a growing trend in the utilization of observational studies that make use of routinely collected healthcare data (RCD). These studies rely on algorithms to identify specific health conditions (e.g. diabetes or sepsis) for statistical analyses. However, there has been substantial variation in the algorithm development and validation, leading to frequently suboptimal performance and posing a significant threat to the validity of study findings. Unfortunately, these issues are often overlooked. Methods We systematically developed guidance for the development, validation, and evaluation of algorithms designed to identify health status (DEVELOP-RCD). Our initial efforts involved conducting both a narrative review and a systematic review of published studies on the concepts and methodological issues related to algorithm development, validation, and evaluation. Subsequently, we conducted an empirical study on an algorithm for identifying sepsis. Based on these findings, we formulated specific workflow and recommendations for algorithm development, validation, and evaluation within the guidance. Finally, the guidance underwent independent review by a panel of 20 external experts who then convened a consensus meeting to finalize it. Results A standardized workflow for algorithm development, validation, and evaluation was established. Guided by specific health status considerations, the workflow comprises four integrated steps: assessing an existing algorithm’s suitability for the target health status; developing a new algorithm using recommended methods; validating the algorithm using prescribed performance measures; and evaluating the impact of the algorithm on study results. Additionally, 13 good practice recommendations were formulated with detailed explanations. Furthermore, a practical study on sepsis identification was included to demonstrate the application of this guidance. Conclusions The establishment of guidance is intended to aid researchers and clinicians in the appropriate and accurate development and application of algorithms for identifying health status from RCD. This guidance has the potential to enhance the credibility of findings from observational studies involving RCD.

Abstract Macrocyclic conformations play a crucial role in regulating their properties. Our understanding of the determinants to control macrocyclic conformation interconversion is still in its infancy. Here we present a macrocycle, octamethyl cyclo[4](1,3-(4,6)-dimethylbenzene)[4]((4,6-benzene)(1,3-dicarboxylate) (OC-4), that can exist at 298 K as two stable atropisomers with C 2v and C 4v symmetry denoted as C 2v - OC-4 and C 4v - OC-4, respectively. Heating induces the efficient stepwise conversion of C 2v - to C 4v - OC-4 via a C s -symmetric intermediate (C s -OC-4). It differs from the typical transition state-mediated processes of simple C–C single bond rotations. Hydrolysis and further esterification with a countercation dependence promote the generation of C 2v - and C s -OC-4 from C 4v - OC-4. In contrast to C 2v - OC-4, C 4v - OC-4 can bind linear guests to form pseudo-rotaxans, or bind C60 or C70 efficiently. The present study highlights the differences in recognition behavior that can result from conformational interconversion, as well as providing insights into the basic parameters that govern coupled molecular rotations.

Abstract The tumor microenvironment (TME) plays a pivotal role in the onset, progression, and treatment response of cancer. Among the various components of the TME, cancer-associated fibroblasts (CAFs) are key regulators of both immune and non-immune cellular functions. Leveraging single-cell RNA sequencing (scRNA) data, we have uncovered previously hidden and promising roles within this specific CAF subgroup, paving the way for its clinical application. However, several critical questions persist, primarily stemming from the heterogeneous nature of CAFs and the use of different fibroblast markers in various sample analyses, causing confusion and hindrance in their clinical implementation. In this groundbreaking study, we have systematically screened multiple databases to identify the most robust marker for distinguishing CAFs in lung cancer, with a particular focus on their potential use in early diagnosis, staging, and treatment response evaluation. Our investigation revealed that COL1A1, COL1A2, FAP, and PDGFRA are effective markers for characterizing CAF subgroups in most lung adenocarcinoma datasets. Through comprehensive analysis of treatment responses, we determined that COL1A1 stands out as the most effective indicator among all CAF markers. COL1A1 not only deciphers the TME signatures related to CAFs but also demonstrates a highly sensitive and specific correlation with treatment responses and multiple survival outcomes. For the first time, we have unveiled the distinct roles played by clusters of CAF markers in differentiating various TME groups. Our findings confirm the sensitive and unique contributions of CAFs to the responses of multiple lung cancer therapies. These insights significantly enhance our understanding of TME functions and drive the translational application of extensive scRNA sequence results. COL1A1 emerges as the most sensitive and specific marker for defining CAF subgroups in scRNA analysis. The CAF ratios represented by COL1A1 can potentially serve as a reliable predictor of treatment responses in clinical practice, thus providing valuable insights into the influential roles of TME components. This research marks a crucial step forward in revolutionizing our approach to cancer diagnosis and treatment.

Abstract Background The high recurrence rate after liver resection emphasizes the urgent need for neoadjuvant therapy in hepatocellular carcinoma (HCC) to enhance the overall prognosis for patients. Immune checkpoint inhibitors, camrelizumab combined with an anti-angiogenic tyrosine kinase inhibitor (TKI) apatinib, have emerged as a first-line treatment option for patients with unresectable HCC, yet its neoadjuvant application in combination with transarterial chemoembolization (TACE) in HCC remains unexplored. Therefore, this study aims to investigate the efficacy and safety of sequential TACE, camrelizumab, and apatinib as a neoadjuvant therapy for single, huge HCC. Methods This multi-center, open-label randomized phase 3 trial will be conducted at 7 tertiary hospitals. Patients with single huge (≥ 10 cm in diameter), resectable HCC will be randomly assigned in a 1:1 ratio to arm of surgery alone or arm of neoadjuvant therapy followed by surgery. In the neoadjuvant therapy group, patients will receive TACE within 1 week after randomization, followed by camrelizumab (200 mg q2w, 4 cycles), along with apatinib (250 mg qd, 2 months). Patients will receive liver resection after neoadjuvant therapy unless the disease is assessed as progressive. The primary outcome is recurrence-free survival (RFS) at 1 year. The planned sample size of 60 patients will be calculated to permit the accumulation of sufficient RFS events in 1 year to achieve 80% power for the RFS primary endpoint. Discussion Synergistic effects provided by multimodality therapy of locoregional treatment, TKI, and anti-programmed cell death 1 inhibitor significantly improved overall survival for patients with unresectable HCC. Our trial will investigate the efficacy and safety of the triple combination of TACE, camrelizumab, and apatinib as a neoadjuvant strategy for huge, resectable HCC. Trial registration www.chitr.org.cn ChiCTR2300078086. Registered on November 28, 2023. Start recruitment: 1st January 2024. Expected completion of recruitment: 15th June 2025.

Abstract Acute myeloid leukemia (AML) remains challenging due to chemotherapeutic drug-resistance (CDR). Aberrant expression B7 family proteins are involved in tumors evasion. We wonder whether B7 family protein alteration in AML CDR further supports tumor escape. Here, we establish AML cytarabine-resistant cell line U937/Ara-C and report on the expression MHC molecule and B7 family member. HLA-ABC was highly expressed similarly on both cell lines. MIC (MHC class I chain related) A/B and B7-H6 was moderately expressed on the surface of U937 and decreased dramatically by U937/Ara-C. In contrast, enhanced expression of B7-H1 and B7-H7 by U937/Ara-C was observed. HLA-DR and other B7 family members including CD80, CD86, B7-DC, B7-H2, B7-H3, B7-H4, and B7-H5 were not detected by both cell lines. Compared co-cultured with U937, peripheral blood mononuclear cells showed a decreased cytotoxicity when incubated with U937/Ara-C, as indicated by decreased levels of granzyme B and perforin production, accompanied with less TNF-α and lactate dehydrogenase secretion. In conclusion, AML CDR further evades the anti-tumor immune response which may through MHC molecule and B7 family members.

Abstract Amine-functionalized adsorbents offer substantial potential for CO2 capture owing to their selectivity and diverse application scenarios. However, their effectiveness is hindered by low efficiency and unstable cyclic performance. Here we introduce an amine-support system designed to achieve efficient and stable CO2 capture. Through atom-level design, each polyethyleneimine (PEI) molecule is precisely impregnated into the cage-like pore of MIL–101(Cr), forming stable composites via strong coordination with unsaturated Cr acid sites within the crystal lattice. The resulting adsorbent demonstrates a low regeneration energy (39.6 kJ/molCO2), excellent cyclic stability (0.18% decay per cycle under dry CO2 regeneration), high CO2 adsorption capacity (4.0 mmol/g), and rapid adsorption kinetics (15 min for saturation at 30 °C). These properties stem from the unique electron-level interaction between the amine and the support, effectively preventing carbamate products’ dehydration. This work presents a feasible and promising cost-effective and sustainable CO2 capture strategy.

Abstract Background Faced with the high cost and limited efficiency of classical randomized controlled trials, researchers are increasingly applying adaptive designs to speed up the development of new drugs. However, the application of adaptive design to drug randomized controlled trials (RCTs) and whether the reporting is adequate are unclear. Thus, this study aimed to summarize the epidemiological characteristics of the relevant trials and assess their reporting quality by the Adaptive designs CONSORT Extension (ACE) checklist. Methods We searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL) and ClinicalTrials.gov from inception to January 2020. We included drug RCTs that explicitly claimed to be adaptive trials or used any type of adaptative design. We extracted the epidemiological characteristics of included studies to summarize their adaptive design application. We assessed the reporting quality of the trials by Adaptive designs CONSORT Extension (ACE) checklist. Univariable and multivariable linear regression models were used to the association of four prespecified factors with the quality of reporting. Results Our survey included 108 adaptive trials. We found that adaptive design has been increasingly applied over the years, and was commonly used in phase II trials (n = 45, 41.7%). The primary reasons for using adaptive design were to speed the trial and facilitate decision-making (n = 24, 22.2%), maximize the benefit of participants (n = 21, 19.4%), and reduce the total sample size (n = 15, 13.9%). Group sequential design (n = 63, 58.3%) was the most frequently applied method, followed by adaptive randomization design (n = 26, 24.1%), and adaptive dose-finding design (n = 24, 22.2%). The proportion of adherence to the ACE checklist of 26 topics ranged from 7.4 to 99.1%, with eight topics being adequately reported (i.e., level of adherence ≥ 80%), and eight others being poorly reported (i.e., level of adherence ≤ 30%). In addition, among the seven items specific for adaptive trials, three were poorly reported: accessibility to statistical analysis plan (n = 8, 7.4%), measures for confidentiality (n = 14, 13.0%), and assessments of similarity between interim stages (n = 25, 23.1%). The mean score of the ACE checklist was 13.9 (standard deviation [SD], 3.5) out of 26. According to our multivariable regression analysis, later published trials (estimated β = 0.14, p

Abstract Photocatalysis through energy transfer has been investigated for the facilitation of [4 + 2] cycloaddition reactions. However, the high reactivity of radical species poses a challenging obstacle to achieving enantiocontrol with chiral catalysts, as no enantioselective examples have been reported thus far. Here, we present the development of catalytic asymmetric [4 + 2] dearomative photocycloaddition involving anthracene and its derivatives with alkenylazaarenes. This accomplishment is achieved by utilizing a cooperative photosensitizer and chiral Brønsted acid catalysis platform. Importantly, this process enables the activation of anthracene substrates through energy transfer from triplet DPZ, thereby initiating a precise and stereoselective sequential transformation. The significance of our work is highlighted by the synthesis of a diverse range of pharmaceutical valuable cycloadducts incorporating attractive azaarenes, all obtained with high yields, ees, and drs. The broad substrate scope is further underscored by successful construction of all-carbon quaternary stereocenters and diverse adjacent stereocenters.

Abstract With the discovery of the therapeutic activity of peptides, they have emerged as a promising class of anti-cancer agents due to their specific targeting, low toxicity, and potential for high selectivity. In particular, as peptide-drug conjugates enter clinical, the coupling of targeted peptides with traditional chemotherapy drugs or cytotoxic agents will become a new direction in cancer treatment. To facilitate the drug development of cancer therapy peptides, we have constructed DCTPep, a novel, open, and comprehensive database for cancer therapy peptides. In addition to traditional anticancer peptides (ACPs), the peptide library also includes peptides related to cancer therapy. These data were collected manually from published research articles, patents, and other protein or peptide databases. Data on drug library include clinically investigated and/or approved peptide drugs related to cancer therapy, which mainly come from the portal websites of drug regulatory authorities and organisations in different countries and regions. DCTPep has a total of 6214 entries, we believe that DCTPep will contribute to the design and screening of future cancer therapy peptides.

Convection-allowing ensemble prediction (CAEP) is an important approach to improve the capability of strong convective weather prediction, and how to construct reasonable initial disturbance is one of the key issues of CAEP. In this paper, the experiments of the per⁃ turbed-observation (PO) method in the CAEP system in the Inner Mongolia region were carried out and evaluated by comparing them with the downscaling (DOWN) method. The performance of the PO method in the CAEP system was then analyzed, which will provide a technical ref⁃ erence for the construction of the CAEP system in Inner Mongolia. The results are as follows. (1) The initial perturbation constructed by the PO method can effectively include the observations in the Inner Mongolia region, which can reduce the uncertainty of the background field and the perturbation has sufficient growth capacity. (2) Compared with the DOWN method, the PO method can significantly reduce the short-term forecast error of CAEP. The root mean square error (RMSE) of upper-level elements is reduced by 4% ~43%, and the RMSE of ground surface elements is reduced by 3% ~9%, suggesting a slightly decreased ensemble spread. The continuous ranked probability score (CRPS) of upper-level elements can be reduced by up to 53% and the CRPS of ground surface elements is reduced by an average of 6%, which generally indicates an improvement in the quality of convective scale ensemble forecasts. (3) The PO method can also improve the capability of short-term precipitation forecasts. The TS score for precipitation levels of 0.1 mm, 4 mm, and 13 mm increased by 0.015, 0.003, and 0.0015, re⁃ spectively. Furthermore, the case study shows that the PO method is more accurate in predicting the precipitation areas and intensity levels.

Abstract Background Clinical scenarios frequently present challenges when patients exhibit asymmetrical mandibular atrophy. The dilemma arises: should we adhere to the conventional All-on-4 technique, or should we contemplate placing vertically oriented implants on the side with sufficient bone mass? This study aims to employ three-dimensional finite element analysis to simulate and explore the biomechanical advantages of each approach. Methods A finite element model, derived from computed tomography (CT) data, was utilized to simulate the nonhomogeneous features of the mandible. Three configurations—All-on-4, All-on-5-v and All-on-5-o were studied. Vertical and oblique forces of 200 N were applied unilaterally, and vertical force of 100 N was applied anteriorly to simulate different masticatory mechanisms. The maximum von Mises stresses on the implant and framework were recorded, as well as the maximum equivalent strain in the peri-implant bone. Results The maximum stress values for all designs were located at the neck of the distal implant, and the maximum strains in the bone tissue were located around the distal implant. The All-on-5-o and All-on-5-v models exhibited reduced stresses and strains compared to All-on-4, highlighting the potential benefits of the additional implant. There were no considerable differences in stresses and strains between the All-on-5-o and All-on-5-v groups. Conclusions With the presence of adequate bone volume on one side and severe atrophy of the contralateral bone, while the “All-on-4 concept” is a viable approach, vertical implant placement optimizes the transfer of forces between components and tissues.

Using the field-theory approach combining bosonization and renormalization group, we investigate the weak-coupling phase diagram of the unconventional Hubbard chain, where in addition to a bond–charge interaction (X), the Hubbard interaction differs between odd (Uo) and even (Ue) sites. The result shows that at quarter filling, the unequal Hubbard repulsion has a great influence on low-energy charge excitations. For the attractive X, the umklapp scattering always exists, and the ground state only exhibits a spin-gapless insulating phase with dominant spin-density-wave correlations. For the repulsive X, the umklapp processes only take place if both Uo and Ue are greater than 8Xcos(π/4), and the phase diagram consists of three phases, a metallic phase with the spin-gapped singlet superconducting correlation, and two insulating phases characterized by the spin-density-wave and charge-density-wave correlations. We also present the phase diagram of the standard t-U-X chain in the case of non-half filling.

Direct air capture (DAC) by solid amine adsorbents is a promising technology to curb the increasing atmospheric CO2 level. Despite extensive efforts, there are still limited improvements for this type of materials in their CO2 uptake and adsorption kinetics under ultra-dilute conditions. And most current research focuses on powdered adsorbents, which need to be granulated or fabricated into devices for DAC application, resulting in a further decline in CO2 uptake. Herein, a series of commercial resin particles (1.0 mm) were used as supports, and it was found that X5 exhibited favorable support characteristics in the preparation of solid amine adsorbents. Notably, X5 possessed a large pore volume of 1.90 cm3/g and featured a hierarchical bimodal porous network comprising mesopores and macropores. The prepared adsorbents (PEI@X5) had considerable polyethyleneimine (PEI) dispersion even at PEI content up to 50 %, and thus demonstrated excellent CO2 adsorption performances with high CO2 uptakes of 118 or 108 mg/g in TGA or fixed bed under simulated ambient air conditions (25 °C, 400 ppm CO2). Additionally, the adsorbents exhibited superb cyclic stability with no decay observed over 10 adsorption-regeneration cycles. The introduction of 25 % relative humidity (RH) of water vapor significantly improved the CO2 uptake of the adsorbent to 130 mg/g, with a lifting efficiency of 20.4 %. However, further increases in RH reduced the CO2 uptake and adsorption rate due to the excessive adsorption water, which leached part of PEI from the pores of 50 %PEI@X5. Considering the commercial production of raw materials, the facile synthesis of 50 %PEI@X5, and its superior CO2 capture efficiency, these findings open up new avenues for DAC technology.

Terpenoids are widely used as medicines, flavors, and biofuels. However, the use of these natural products is largely restricted by their low abundance in native plants. Fortunately, heterologous biosynthesis of terpenoids in microorganisms offers an alternative and sustainable approach for efficient production. Various genome-editing technologies have been developed for microbial strain construction. Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR associated protein 9 (Cas9) is the most commonly used system owing to its outstanding efficiency and convenience in genome editing. In this review, the basic principles of CRISPR-Cas9 systems are briefly introduced and their applications in engineering bacteria for the production of plant-derived terpenoids are summarized. The aim of this review is to provide an overview of the current developments of CRISPR-Cas9-based genome-editing technologies in bacterial engineering, concluding with perspectives on the challenges and opportunities of these technologies.

Abstract Background As the leading cause of end‐stage liver disease, nonalcoholic fatty liver disease (NAFLD) is mainly induced by lipid dyshomeostasis. The translation of endogenous circular RNAs (circRNAs) is closely related to the progression of various diseases, but the involvement of circRNAs in NAFLD has not been determined. Methods Combined high‐throughput circRNA profiles were used to identify circRNAs with translational potential. The underlying molecular mechanisms were investigated by RNA sequencing, pull‐down/MS and site‐specific mutagenesis. Results In this study, we focused on circ‐SLC9A6, an abnormally highly expressed circRNA in human and mouse liver tissue during NAFLD development that exacerbates metabolic dyshomeostasis in hepatocytes by encoding a novel peptide called SLC9A6‐126aa in vivo and in vitro. YTHDF2‐mediated degradation of m6A‐modified circ‐SLC9A6 was found to be essential for the regulation of SLC9A6‐126aa expression. We further found that the phosphorylation of SLC9A6‐126aa by AKT was crucial for its cytoplasmic localization and the maintenance of physiological homeostasis, whereas high‐fat stress induced substantial translocation of unphosphorylated SLC9A6‐126aa to the nucleus, resulting in a vicious cycle of lipid metabolic dysfunction. Nuclear SLC9A6‐126aa promotes transcriptional activation of the target gene CD36 and enhances its occupancy of the CD36 promoter locus by regulating MOF‐mediated histone H4K16 acetylation. Hepatic CD36 depletion significantly ameliorated hyperactivated MAPK signalling and lipid disturbance in SLC9A6‐126aa transgenic mice. Clinically, increasing levels of SLC9A6‐126aa were observed during NAFLD progression and were found to be positively correlated with the CD36 and MAPK cascades. Conclusion This study revealed the role of circ‐SLC9A6‐derived SLC9A6‐126aa in the epigenetic modification‐mediated regulation of lipid metabolism. Our findings may provide promising therapeutic targets for NAFLD and new insights into the pathological mechanisms of metabolic diseases. Highlights Under normal circumstances, driven by m6A modification, YTHDF2 directly recognizes and degrades circ‐SLC9A6, thereby inhibiting the translation of SLC9A6‐126aa. Additionally, AKT1 phosphorylates and inhibits the nuclear translocation of SLC9A6‐126aa. In NAFLD, lipid overload leads to YTHDF2 and AKT1 deficiency, ultimately increasing the expression and nuclear import of SLC9A6‐126aa. Nuclear SLC9A6‐126aa binds directly to the CD36 promoter and initiates CD36 transcription, which induces lipid dyshomeostasis.

BackgroundDiabetic retinopathy (DR) is a serious microvascular complication of diabetes mellitus. Research has identified a close relationship between fibroblast growth factor 21 (FGF21) and DR. FGF21 is a member of the FGF subfamily, which is activated by the Klotho coenzyme involved in the occurrence of DR. However, the association between FGF21, Klotho, and DR remains controversial.AimTo assess FGF21 and Klotho levels in patients with DR.MethodsA literature search of the Web of Science, Wiley Online Library, PubMed, China National Knowledge Infrastructure and Wanfang databases was performed. The title or abstract search terms “diabetic retinopathy” and “DR” were used in combination with “fibroblast growth factor 21”, “FGF21”, and “Klotho”. Meta-analysis results are presented as standardized mean difference (SMD) with corresponding 95% confidence interval (CI).ResultsFifteen studies were included in this meta-analysis. FGF21 levels in patients with DR were significantly higher than in non-DR patients with diabetes (SMD: 2.12, 95% CI [1.40, 2.84]). Klotho levels in patients with DR were significantly lower than in non-DR patients with diabetes (SMD: –0.63, 95% CI [–1.22, – 0.04]).ConclusionsThis systematic review is the first to evaluate the relationship between FGF21, Klotho levels, and DR. FGF21 levels were significantly higher in patients with DR. Fully elucidating the role of FGF21 will significantly contribute to the treatment of DR.

ObjectiveThe study aimed to explore the relationship between systemic inflammatory response index (SIRI) levels and osteoarthritis (OA) using cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2018.MethodsUsing cross-sectional data from the NHANES database from 2005 to 2018, we included 11,381 study participants divided into OA (n = 1,437) and non-OA (n = 9,944) groups. Weighted multivariable regression models and subgroup analyses were employed to investigate the relationship between SIRI and OA. Additionally, restricted cubic spline models were used to explore nonlinear relationships.ResultsThis study enrolled 11,381 participants aged ≥20 years, including 1,437 (14%) with OA. Weighted multivariable regression analysis in the fully adjusted Model 3 indicated a correlation between higher levels of SIRI (log2-transformed) and an increased OA risk (odds ratio: 1.150; 95% confidence interval: 1.000–1.323, p 0.05). Additionally, a restricted cubic spline model revealed a nonlinear relationship between log2(SIRI) and OA risk, with a threshold effect showing 4.757 as the critical value of SIRI. SIRI 4.757 showed rapidly increasing OA risk.ConclusionThe positive correlation between SIRI and OA risk, with a critical value of 4.757, holds clinical value in practical applications. Additionally, our study indicates that SIRI is a novel, clinically valuable, and convenient inflammatory biomarker that can be used to predict OA risk in adults.

Background: Benzo(a)pyrene (B[a]P) is the most widely concerned polycyclic aromatic hydrocarbons (PAHs), which metabolizes benzo(a)pyrene-7,8-dihydrodiol-9,10-epoxide (BPDE) in vivo to produce carcinogenic effect on the body. Currently, there is limited research on the role of the variation of metabolic enzymes in this process. Methods: We carried out a study including 752 participants, measured the concentrations of 16 kinds PAHs in both particle and gaseous phases, urinary PAHs metabolites, leukocyte BPDE-DNA adduct and serum BPDE- Albumin (BPDE-Alb) adduct, and calculated daily intake dose (DID) to assess the cumulative exposure of PAHs. We conducted single nucleotide polymorphism sites (SNPs) of metabolic enzymes, explored the exposure–response relationship between the levels of exposure and BPDE adducts using multiple linear regression models. Result: Our results indicated that an interquartile range (IQR) increase in B[a]P, PAHs, BaPeq, 1-hydroxypyrene (1-OHP), 1-hydroxynaphthalene (1-OHNap) and 2-hydroxynaphthalene (2-OHNap) were associated with 26.53 %, 24.24 %, 28.15 %, 39.15 %, 12.85 % and 14.09 % increase in leukocyte BPDE-DNA adduct (all P 0.05). Besides, we also found the polymorphism of CYP1A1(Gly45Asp), CYP2C9 (Ile359Leu), and UGT1A1(downstream) may affect BPDE adducts level. Conclusion: Our results indicated that leukocyte BPDE-DNA adduct could better reflect the exposure to PAHs. Furthermore, the polymorphism of CYP1A1, CYP2C9 and UGT1A1affected the content of BPDE adducts.

Abstract Environmental change exerts a profound effect on soil microbial domains—including bacteria, fungi, and protists—that each perform vital ecological processes. While these microbial domains are ubiquitous and extremely diverse, little is known about how they respond to environmental changes in urban soil ecosystems and what ecological processes shape them. Here we investigated the community assembly processes governing bacteria, fungi, and protists through the lens of four distinct subcommunities: abundant, conditionally rare, conditionally abundant, and rare taxa. We show that transient taxa, including the conditionally rare and conditionally rare or abundant taxa, were the predominant subcommunities. Deterministic processes (e.g., environmental filtering) had major roles in structuring all subcommunities of fungi, as well as conditionally rare and abundant protists. Stochastic processes had strong effects in structuring all subcommunities of bacteria (except rare taxa) and conditionally rare protists. Overall, our study underscores the importance of complementing the traditional taxonomy of microbial domains with the subcommunity approach when investigating microbial communities in urban soil ecosystems.

As a novel economic form, the digital economy plays an important role in promoting urban low-carbon sustainable development (LCSD). Based on panel data from 270 cities in China from 2011 to 2021, this study used principal component analysis and the global entropy weight method to calculate the level of digital economy development and LCSD as well as to empirically discuss any correlated effects and mechanisms. The research showed that the digital economy has significantly promoted urban LCSD and has become an important source for promoting green low-carbon development. The digital economy can indirectly promote LCSD by accelerating industrial structure upgrading and promoting technological innovation; Moreover, this promotion can show significant threshold characteristics with these factors. When industrial structure upgrading and technological innovation reach a certain threshold, the digital economy can further enhance urban LCSD. The promotion of the digital economy is positively influenced by marketization level and environmental regulation, and it exhibits distinct regional characteristics. During the critical period of economic development and transformation, the government must continuously promote the development of the digital economy, fully release its dividends on LCSD, and implement a differentiated digital development strategy to promote low-carbon economic development according to local conditions.

Abstract The Seychelles magpie‐robin's (SMR) five island populations exhibit some of the lowest recorded levels of genetic diversity among endangered birds, and high levels of inbreeding. These populations collapsed during the 20th century, and the species was listed as Critically Endangered in the IUCN Red List in 1994. An assisted translocation‐for‐recovery program initiated in the 1990s increased the number of mature individuals, resulting in its downlisting to Endangered in 2005. Here, we explore the temporal genomic erosion of the SMR based on a dataset of 201 re‐sequenced whole genomes that span the past ~150 years. Our sample set includes individuals that predate the bottleneck by up to 100 years, as well as individuals from contemporary populations established during the species recovery program. Despite the SMR's recent demographic recovery, our data reveal a marked increase in both the genetic load and realized load in the extant populations when compared to the historical samples. Conservation management may have reduced the intensity of selection by increasing juvenile survival and relaxing intraspecific competition between individuals, resulting in the accumulation of loss‐of‐function mutations (i.e. severely deleterious variants) in the rapidly recovering population. In addition, we found a 3‐fold decrease in genetic diversity between temporal samples. While the low genetic diversity in modern populations may limit the species' adaptability to future environmental changes, future conservation efforts (including IUCN assessments) may also need to assess the threats posed by their high genetic load. Our computer simulations highlight the value of translocations for genetic rescue and show how this could halt genomic erosion in threatened species such as the SMR.

IntroductionTuberculosis (TB) stands as a paramount global health concern, contributing significantly to worldwide mortality rates. Effective containment of TB requires deployment of cost-efficient screening method with limited resources. To enhance the precision of resource allocation in the global fight against TB, this research proposed chest X-ray radiography (CXR) based machine learning screening algorithms with optimization, benchmarking and tuning for the best TB subclassification tasks for clinical application.MethodsThis investigation delves into the development and evaluation of a robust ensemble deep learning framework, comprising 43 distinct models, tailored for the identification of active TB cases and the categorization of their clinical subtypes. The proposed framework is essentially an ensemble model with multiple feature extractors and one of three fusion strategies-voting, attention-based, or concatenation methods-in the fusion stage before a final classification. The comprised de-identified dataset contains records of 915 active TB patients alongside 1,276 healthy controls with subtype-specific information. Thus, the realizations of our framework are capable for diagnosis with subclass identification. The subclass tags include: secondary tuberculosis/tuberculous pleurisy; non-cavity/cavity; secondary tuberculosis only/secondary tuberculosis and tuberculous pleurisy; tuberculous pleurisy only/secondary tuberculosis and tuberculous pleurisy.ResultsBased on the dataset and model selection and tuning, ensemble models show their capability with self-correction capability of subclass identification with rendering robust clinical predictions. The best double-CNN-extractor model with concatenation/attention fusion strategies may potentially be the successful model for subclass tasks in real application. With visualization techniques, in-depth analysis of the ensemble model's performance across different fusion strategies are verified.DiscussionThe findings underscore the potential of such ensemble approaches in augmenting TB diagnostics with subclassification. Even with limited dataset, the self-correction within the ensemble models still guarantees the accuracies to some level for potential clinical decision-making processes in TB management. Ultimately, this study shows a direction for better TB screening in the future TB response strategy.

IntroductionSepsis is a syndrome of organ dysfunction caused by a dysregulated host response to infection and septic shock. Currently, antibiotic therapy is the standard treatment for sepsis, but it can lead to drug resistance. The disturbance of the gut microbiota which is affected by sepsis could lead to the development of organ failure. It is reported that probiotics could shape the gut microbiota, potentially controlling a variety of intestinal diseases and promoting whole-body health.MethodsIn this study, we evaluated the preventive effects of intra- and extracellular products of probiotics on sepsis. The extracellular products of Lactococcus lactis (L. lactis) were identified through the in vivo cell experiments. The preventive effect and mechanism of L. lactis extracellular products on mouse sepsis were further explored through HE staining, mouse survival rate measurement, chip analysis, etc.ResultsL. lactis extracellular products increase cell survival and significantly reduce inflammatory factors secreted in a cellular sepsis model. In in vivo experiments in mice, our samples attenuated sepsis-induced pulmonary edema and inflammatory infiltrates in the lungs of mice, and reduced mortality and inflammatory factor levels within the serum of mice. Finally, the mechanism of sepsis prevention by lactic acid bacteria is suggested. Extracellular products of L. lactis could effectively prevent sepsis episodes.DiscussionIn animal experiments, we reported that extracellular products of L. lactis can effectively prevent sepsis, and preliminarily discussed the pathological mechanism, which provides more ideas for the prevention of sepsis. In the future, probiotics may be considered a new way to prevent sepsis.

ObjectivesTo analyze the costs and medication patterns of patients with chronic kidney disease (CKD) and comorbidities in Xuzhou, China, using a large electronic medical records database.MethodsData were obtained from an electronic medical records database. The annual per-person and per-visit cost of hospitalization, as well as the proportions of those costs, are presented.ResultsThe majority of the participants were middle-aged men, and had medical insurance. Glomerulonephritis was the primary cause of CKD in patients with an identified etiology. The average per-visit cost of hospitalization for the CKD-renal anemia and CKD-mineral and bone disorder groups was 8,674.5 (5,154.3–13,949.6) and 8,182.6 (4,798.2–12,844.7) Yuan, respectively, which was greater than that of the other groups. The major expenses incurred were for diagnostics, drug usage, surgical procedures, laboratory tests and material costs.ConclusionThe substantial burden imposed by CKD with comorbidities indicates the importance of implementing public health strategies aimed at detecting and preventing these conditions in the general population. With the aging population, our nation may experience a greater CKD-related economic burden.

ObjectiveThis study aims to compare the utilization of 3D-CT reconstruction in measuring pedicle outer width (POW) between younger/middle-aged patients ( 0.05). In the observation group, both male and female patients had significantly smaller POW compared to the control group (P 0.05). In the observation group, the POW was less than 5 mm in 9.33% (81/868) of cases and less than 7 mm in 49.88% (433/868) of cases, primarily observed from T11 to L3. In the control group, 4.81% (31/644) of cases had a POW of less than 5 mm, and 13.81% (88/644) had a POW of less than 7 mm.ConclusionUtilizing preoperative 3D-CT reconstruction to measure POW in patients with TSF not only facilitates the assessment of surgical feasibility but also aids in surgical pathway planning, thus potentially reducing the incidence of postoperative complications.

Abstract Cigarette smoke (CS) has been generally recognized as a chief carcinogenic factor in renal cell carcinoma (RCC). The stimulative effect of CS on renal cancer stem cells (RCSCs) has been described previously. The Sonic Hedgehog (SHH) pathway plays an essential role in self-renewal, cell growth, drug resistance, metastasis, and recurrence of cancer stem cells (CSCs). Renal cancer-related gene ΔNp63α is highly expressed in renal epithelial tissues and contributes to the RCSCs characteristics of tumors. The aim of this study was to elucidate the role of ΔNp63α and the SHH pathway on the activity of RCSCs induced by CS through a series of in vivo and in vitro studies. It was shown that in renal cancer tissues, ΔNp63α and RCSCs markers in smokers are expressed higher than that in non-smokers. RCSCs were effectively enriched by tumor sphere formation assay. Besides, CS increased the expression of RCSCs markers and the capability of sphere-forming in vitro and in vivo. Moreover, the SHH pathway was activated, and the specialized inhibitor alleviated the promotion of CS on RCSCs. ΔNp63α activated the SHH pathway and promoted CS-induced enhancement of RCSCs activity. These findings indicate that ΔNp63α positively regulates the activity of CS-induced RCSCs via the SHH pathway.

Parkinson's disease (PD) poses a significant challenge in neurodegenerative disorders, characterized by the progressive loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNc). The intricate mechanisms orchestrating DA neurodegeneration in PD are not fully understood, necessitating the exploration of innovative therapeutic approaches. Recent studies have implicated ferroptosis as a major contributor to the loss of DA neurons, revealing a complex interplay between iron accumulation and neurodegeneration. However, the sophisticated nature of this process challenges the conventional belief that mere iron removal could effectively prevent DA neuronal ferroptosis. Here, we report JWA, alternatively referred to as ARL6IP5, as a negative regulator of ferroptosis, capable of ameliorating DA neuronal loss in the context of PD. In this study, synchronized expression patterns of JWA and tyrosine hydroxylase (TH) in PD patients and mice were observed, underscoring the importance of JWA for DA neuronal survival. Screening of ferroptosis-related genes unraveled the engagement of iron metabolism in the JWA-dependent inhibition of DA neuronal ferroptosis. Genetic manipulation of JWA provided compelling evidence linking its neuroprotective effects to the attenuation of NCOA4-mediated ferritinophagy. Molecular docking, co-immunoprecipitation, and immunofluorescence studies confirmed that JWA mitigated DA neuronal ferroptosis by occupying the ferritin binding site of NCOA4. Moreover, the JWA-activating compound, JAC4, demonstrated promising neuroprotective effects in cellular and animal PD models by elevating JWA expression, offering a potential avenue for neuroprotection in PD. Collectively, our work establishes JWA as a novel regulator of ferritinophagy, presenting a promising therapeutic target for addressing DA neuronal ferroptosis in PD.

Abstract While many studies have sought to explore the degree to which sarcopenia-related traits are associated with cognitive performance, these studies have yielded contradictory results without any clear indication of the causality of such relationships. In efforts to better understand associations between sarcopenia-related traits and cognitive ability, a series of multivariate linear regression assessments were carried out upon datasets derived through the National Health and Nutrition Examination Survey (NHANES). Of these, cognitive performance was assessed by the Digit Symbol Substitution Test (DDST), the Consortium to Establish a Registry for Alzheimer’s Disease Immediate Recall Test (CERAD-IR), Delayed Recall Test (CERAD-DR) and Animal Fluency Test (AFT). Causal relationships between the two were further inferred via a two-sample Mendelian randomization (MR) analysis approach. Sarcopenia-related traits considered in these assessments included walking speed, appendicular skeletal muscle mass (ASM), and hand grip strength (HGS). Walking speed, ASM, and HGS were all significantly independently related to cognitive scores following adjustment for covariates. MR assessments also identified that each 1-SD higher walking speed and appendicular lean mass were causally and respectively associated with a 0.34 [standard error (SE) = 0.09; p

Abstract Background Chronic obstructive pulmonary disease (COPD) is a common respiratory disease and the third leading cause of death worldwide. Previous evidence has shown that acupuncture may be an effective complementary alternative therapy for stable COPD. However, large-sample, rigorously designed long-term follow-up studies still need to be completed. Notably, the relationship between the frequency of acupuncture and clinical efficacy in studies on acupuncture for stable COPD still needs further validation. This study aims to evaluate the efficacy and safety of acupuncture for stable COPD and further investigate the dose–effect relationship of acupuncture. Methods/design This is a multicenter, randomized, controlled trial that uses central randomization to randomly allocate 550 participants in a 1:1:1:1:1 ratio to once a week acupuncture group, twice a week acupuncture group, three times a week acupuncture group, sham acupuncture group and waiting-list control group. The sham acupuncture group will receive placebo acupuncture treatments three times per week, and the waiting-list control group will not receive any form of acupuncture intervention. The study consists of a 2-week baseline, 12-week of treatment, and 52-week of follow-up. Patients with COPD between 40 to 80 years old who have received stable Western medication within the previous 3 months and have had at least 1 moderate or severe acute exacerbation within the past 1 year will be included in the study. Basic treatment will remain the same for all participants. The primary outcome is the proportion of responders at week 12. Secondary outcomes include the proportion of responders at week 64, change in the St. George's Respiratory Questionnaire (SGRQ) Scale, change in the Modified-Medical Research Council (mMRC) Scale, change in the COPD Assessment Test (CAT) Scale, change in the Lung Function Screening Indicators (LFSI), change in the 6-min walk distance (6-MWD), change in Short-Form 36 Health Survey (SF-36) Scale, the number of moderate and severe acute exacerbations and adverse event rate during the follow-up period. Discussion This study will provide robust evidence on whether acupuncture is safe and effective for treating stable COPD. Meanwhile, comparing the differences in efficacy between different acupuncture frequencies will further promote the optimization of acupuncture for stable COPD. Trial registration This study was registered in the Chinese Clinical Trial Registry (ChiCTR2200058757), on April 16, 2022.

Abstract Introduction Interrupted time series (ITS) design is a commonly used method for evaluating large-scale interventions in clinical practice or public health. However, improperly using this method can lead to biased results. Objective To investigate design and statistical analysis characteristics of drug utilization studies using ITS design, and give recommendations for improvements. Methods A literature search was conducted based on PubMed from January 2021 to December 2021. We included original articles that used ITS design to investigate drug utilization without restriction on study population or outcome types. A structured, pilot-tested questionnaire was developed to extract information regarding study characteristics and details about design and statistical analysis. Results We included 153 eligible studies. Among those, 28.1% (43/153) clearly explained the rationale for using the ITS design and 13.7% (21/153) clarified the rationale of using the specified ITS model structure. One hundred and forty-nine studies used aggregated data to do ITS analysis, and 20.8% (31/149) clarified the rationale for the number of time points. The consideration of autocorrelation, non-stationary and seasonality was often lacking among those studies, and only 14 studies mentioned all of three methodological issues. Missing data was mentioned in 31 studies. Only 39.22% (60/153) reported the regression models, while 15 studies gave the incorrect interpretation of level change due to time parameterization. Time-varying participant characteristics were considered in 24 studies. In 97 studies containing hierarchical data, 23 studies clarified the heterogeneity among clusters and used statistical methods to address this issue. Conclusion The quality of design and statistical analyses in ITS studies for drug utilization remains unsatisfactory. Three emerging methodological issues warranted particular attention, including incorrect interpretation of level change due to time parameterization, time-varying participant characteristics and hierarchical data analysis. We offered specific recommendations about the design, analysis and reporting of the ITS study.

Abstract Background Epithelioid sarcoma is a rare soft tissue sarcoma characterized by SMARCB1/INI1 deficiency. Much attention has been paid to the selective EZH2 inhibitor tazemetostat, where other systemic treatments are generally ignored. To explore alternative treatment options, we studied the effects of irinotecan-based chemotherapy in a series of epithelioid sarcoma patients. Methods We retrospectively reviewed data from patients with metastatic or unresectable epithelioid sarcoma at the Peking University People’s Hospital treated with irinotecan (50 mg/m2/d d1-5 Q3W) in combination with Anlotinib (12 mg Qd, 2 weeks on and 1 week off) from July 2015 to November 2021. Results A total of 54 courses were administered. With a median follow up of 21.2 months (95% CI, 12.2, 68.1), the 5-year overall survival rate was 83.3%. Five of eight (62.5%) patients presented with unresectable localized lesions, including local tumor thrombosis and lymphatic metastasis. The other patients had unresectable pulmonary metastases. Six of eight (75%) patients had progressed following two lines of systemic therapy. The objective response rate reached 37.5% (three of eight patients) while stabilized disease was observed in 62.5% (five of eight) of patients. No patient had progressed at initial evaluation. At the last follow up, two patients were still using the combination and three patients had ceased the therapy due to toxicities such as diarrhea, nausea, and emesis. One patient changed to tazemetostat for maintenance and one patient stopped treatment due to coronavirus disease 2019 (COVID-19). Another patient stopped therapy as residual lesions had been radiated. Conclusions The combination of irinotecan and Anlotinib as a salvage regimen may be considered another effective treatment option for refractory epithelioid sarcoma. Trial registration This study was approved in the Medical Ethics Committee of Peking University People’s Hospital on October 28, 2022 (No.: 2022PHD015-002). The study was registered in Clinicaltrials.gov with identifier no. NCT05656222.

Abstract Background This study investigated the effects of authoritarian filial piety (AFP) and caregiver self-efficacy on the caregiving experience of adult children of physically impaired older adults. Socio-cultural stress and coping model was applied to test the influence of AFP on caregiver gains. Methods A total of 601 Chinese adult children caregivers and care-recipient dyads participated in this cross-sectional study in 2021. Four instruments were used to collect data: the 4-item Zarit Burden Interview, Positive Aspects of Caregiving Scale, Caregiver Task Inventory Scale, and Authoritarian Filial Piety Scale. All mediation and moderated mediation effects were estimated using SPSS 26.0. Results Caregiver self-efficacy was found to not only mediate but also help family caregivers convert their burden into positive gains. AFP moderates the association between caregiver burden and self-efficacy, as well as between caregiver burden and caregiver gains. Conclusions This study provides valuable insights into filial piety, elucidating AFP’s comprehensive impact on cognitive appraisals of caregiving. Culturally sensitive psychoeducational therapy, addressing AFP expectations and boosting caregiver self-efficacy, is recommended to enhance positive caregiving outcomes.

Abstract Springtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data.

Abstract Background Populus simonii × P. nigra is an ideal material for studying the molecular mechanisms of woody plants. In recent years, research on Populus simonii × P. nigra has increasingly focused on the application of transgenic technology to improve salt tolerance. However, the rapid characterization of gene functions has been hampered by the long growth cycle and exceedingly poor transformation efficiency. Protoplasts are an important tool for plant gene engineering, which can assist with challenging genetic transformation and the protracted growth cycle of Populus simonii × P. nigra. This study established an optimized system for the preparation and transformation of protoplasts from Populus simonii × P. nigra leaves, making genetic research on Populus simonii × P. nigra faster and more convenient. Major Latex Protein (MLP) family genes play a crucial role in plant salt stress response. In the previous study, we discovered that PsnMLP328 can be induced by salt treatment, which suggested that this gene may be involved in response to salt stress. Protein localization is a suggestion for its function. Therefore, we conducted subcellular localization analysis using protoplasts of Populus simonii × P. nigra to study the function of the PsnMLP328 gene preliminarily. Results This study established an optimized system for the preparation and transformation of Populus simonii × P. nigra protoplasts. The research results indicate that the optimal separation scheme for the protoplasts of Populus simonii × P. nigra leaves included 2.5% cellulase R-10, 0.6% macerozyme R-10, 0.3% pectolyase Y-23, and 0.8 M mannitol. After enzymatic digestion for 5 h, the yield of obtained protoplasts could reach up to 2 × 107 protoplasts/gFW, with a high viability of 98%. We carried out the subcellular localization analysis based on the optimized transient transformation system, and the results indicated that the MLP328 protein is localized in the nucleus and cytoplasm; thereby proving the effectiveness of the transformation system. Conclusion In summary, this study successfully established an efficient system for preparing and transforming leaf protoplasts of Populus simonii × P. nigra, laying the foundation for future research on gene function and expression of Populus simonii × P. nigra.

Lithium-ion battery (LIB) is the key technology for climate change mitigation. The sustainability of LIB supply chain has caused widespread concern since the material utilization efficiency of LIB supply chain has not been well investigated. This study aims to fill this research gap by conducting a dynamic material flow analysis of lithium in China from 2015 to 2021. Results indicate that within the temporal boundary, lithium flow and in-use stock grew significantly in China due to the rapid development of the EV market, with lithium flow in domestic production of basic chemicals increasing by 614% to 100 kt, end-use consumption increasing by 160% to 35 kt, and in-use stock increasing by 62% to 195 kt. China has been a net importer of lithium, of which cumulative imports and exports were 343 kt and 169 kt, respectively. In addition, 103 kt of lithium was converted to inventories or was lost during the processing from 2015 to 2021. By optimizing inventory and processing, developing substitutes for lithium for non-battery applications, and improving lithium recycling, China's net import dependency of lithium could be reduced from 27%-86% to 0%-16%. Our study demonstrates that it is urgent to improve material utilization efficiency so that the lithium resource supply can be secured.

The implementation of a machine-vision system for real-time precision weed management is a crucial step towards the development of smart spraying robotic vehicles. The intelligent machine-vision system, constructed using deep learning object detection models, has the potential to accurately detect weeds and crops from images. Both data-centric and model-centric approaches of deep learning model development offer advantages depending on environment and non-environment factors. To assess the performance of weed detection in real-field conditions for eight crop species, the Yolov8, Yolov9, and customized Yolov9 deep learning models were trained and evaluated using RGB images from four locations (Casselton, Fargo, and Carrington) over a two-year period in the Great Plains region of the U.S. The experiment encompassed eight crop species—dry bean, canola, corn, field pea, flax, lentil, soybean, and sugar beet—and five weed species—horseweed, kochia, redroot pigweed, common ragweed, and water hemp. Six Yolov8 and eight Yolov9 model variants were trained using annotated weed and crop images gathered from four different sites including combined dataset from four sites. The Yolov8 and Yolov9 models’ performance in weed detection were assessed based on mean average precision (mAP50) metrics for five datasets, eight crop species, and five weed species. The results of the weed and crop detection evaluation showed high mAP50 values of 86.2 %. The mAP50 values for individual weed and crop species detection ranged from 80.8 % to 98 %. The results demonstrated that the performance of the model varied by model type (model-centric), location due to environment (data-centric), data size (data-centric), data quality (data-centric), and object size in the image (data-centric). Nevertheless, the Yolov9 customized lightweight model has the potential to play a significant role in building a real time machine-vision-based precision weed management system.

Traditional weed management often involves blanket herbicide spraying, resulting in substantial herbicide wastage, environmental concerns, and herbicide resistant issues. Smart spraying systems utilizing robotics and sensors technologies can minimize herbicide usage and provide a sustainable solution for site-specific weed management. A machine vision-based spraying system was designed and developed for weed identification and precise spray application onto the target weeds. The sprayer platform utilizes a deep learning YOLOv4 model to accurately recognize multiple weed species, facilitating targeted spray application. The platform is equipped with an FLIR RGB camera for real-time image acquisition and Nvidia Jetson AGX Orin edge device for deploying weed detection deep-learning model. The GPIO pins of Nvidia Jetson were utilized to activate relay, providing precise on/off control over the TeeJet solenoid valves for spot spraying. Both indoor and field experiments were conducted to evaluate and compare the performance of vision-based sprayer system for weed identification and precise spraying onto the target weeds. In the indoor experiment, the sprayer system showed the average effective spraying rate of 93.33 %, with the precision of 100 % and recall of 92.8 %. Conversely, the field experiment resulted in a slightly lower average effective spraying rate of 90.6 %, while maintaining a precision of 95.5 % and a recall of 89.47 %. The reduced accuracy of the spraying system in field experiment was due to varying outdoor conditions such as lighting, shadows, and wind velocity. Overall, the result of this study demonstrates the spraying system's potential for targeted herbicide application onto the grid cells containing weeds, effectively reducing herbicide usage and overall weed management costs.

AbstractObjective The aim of this retrospective study was to investigate the short-term and long-term efficacy of high-intensity focused ultrasound (HIFU) therapy for abdominal wall endometriosis (AWE) and explore its potential influencing factors.Materials and methods A total of 80 patients with AWE who underwent HIFU therapy were retrospectively analyzed. Follow-ups were also conducted to evaluate the changes in lesion size and pain relief. Multivariate logistic regression analysis was applied to investigate factors influencing HIFU therapy for AWE.Results Among the 80 patients with AWE who received HIFU therapy, the effective rates were 76.3%, 80.5%, and 90.5% after 3, 12 and 24 months of follow-up, respectively. Multivariate logistic regression analysis revealed that the AWE lesion diameter and sonication intensity had statistically significant effects on the 3-month and 12-month efficacy of HIFU therapy for AWE, while age, BMI, disease duration, average sonication power and grey-scale changes did not have statistically significant effects. Four patients with AWE experienced recurrence after HIFU therapy, for a three-year cumulative recurrence rate of 6.3%. Furthermore, ten patients required reintervention after treatment, for a five-year cumulative reintervention rate of 13.9%.Conclusions This study further confirmed the safety and effectiveness of HIFU therapy for AWE. Factors such as AWE lesion diameter and sonication intensity have been identified as key influencers affecting the short-term and long-term efficacy of HIFU therapy for AWE. The first two years following HIFU therapy constitute crucial periods for observation, and judiciously extending follow-up intervals during this timeframe is advised.

WeedCube dataset consists of hyperspectral images of three crops (canola, soybean, and sugarbeet) and four invasive weeds species (kochia, common waterhemp, redroot pigweed, and common ragweed). Plants were grown in two separate greenhouses and plant canopies were captured from a top-down camera angle. A push-broom hyperspectral sensor in the visible near infrared region of 400–1000 nm was used for data collection. The dataset includes 160 calibrated images. The number of images can be further increased by selection of smaller region of interests (ROIs). Dataset is supplemented by Jupyter Notebook scripts that help in data augmentation, spectral pre-processing, ROI selection for points and images, and data visualization. The primary purpose of this dataset is to support weed classification or identification studies by enhancing existing training datasets and validating the generalization capabilities of existing models. Owing to the three-dimensional (3D) nature of hyperspectral images, this dataset can also be utilized by researchers and educators across various domains for the development and testing of deep learning algorithms, the creation of automated data processing pipelines effective for 3D data, the development of tools for 3D data visualization, the creation of innovative solutions for data compression, and addressing system memory issues associated with high-dimensional data.

Abstract BackgroundLarge language models (LLMs) have achieved great progress in natural language processing tasks and demonstrated the potential for use in clinical applications. Despite their capabilities, LLMs in the medical domain are prone to generating hallucinations (not fully reliable responses). Hallucinations in LLMs’ responses create substantial risks, potentially threatening patients’ physical safety. Thus, to perceive and prevent this safety risk, it is essential to evaluate LLMs in the medical domain and build a systematic evaluation. ObjectiveWe developed a comprehensive evaluation system, MedGPTEval, composed of criteria, medical data sets in Chinese, and publicly available benchmarks. MethodsFirst, a set of evaluation criteria was designed based on a comprehensive literature review. Second, existing candidate criteria were optimized by using a Delphi method with 5 experts in medicine and engineering. Third, 3 clinical experts designed medical data sets to interact with LLMs. Finally, benchmarking experiments were conducted on the data sets. The responses generated by chatbots based on LLMs were recorded for blind evaluations by 5 licensed medical experts. The evaluation criteria that were obtained covered medical professional capabilities, social comprehensive capabilities, contextual capabilities, and computational robustness, with 16 detailed indicators. The medical data sets include 27 medical dialogues and 7 case reports in Chinese. Three chatbots were evaluated: ChatGPT by OpenAI; ERNIE Bot by Baidu, Inc; and Doctor PuJiang (Dr PJ) by Shanghai Artificial Intelligence Laboratory. ResultsDr PJ outperformed ChatGPT and ERNIE Bot in the multiple-turn medical dialogues and case report scenarios. Dr PJ also outperformed ChatGPT in the semantic consistency rate and complete error rate category, indicating better robustness. However, Dr PJ had slightly lower scores in medical professional capabilities compared with ChatGPT in the multiple-turn dialogue scenario. ConclusionsMedGPTEval provides comprehensive criteria to evaluate chatbots by LLMs in the medical domain, open-source data sets, and benchmarks assessing 3 LLMs. Experimental results demonstrate that Dr PJ outperforms ChatGPT and ERNIE Bot in social and professional contexts. Therefore, such an assessment system can be easily adopted by researchers in this community to augment an open-source data set.

Abstract An accurate quantification of global methane sources and sinks is imperative for assessing realistic pathways to mitigate climate change. A key challenge of quantifying the Global Methane Budget (Saunois et al., 2020, https://doi.org/10.5194/essd‐12‐1561‐2020) is the lack of consistency in uncertainties between sectors. Here we provide a new perspective on bottom‐up (BU) and top‐down (TD) methane uncertainties by using an expert opinion analysis based on a questionnaire conducted in 2021. Expectedly, experts rank highest uncertainty and lowest confidence levels in the Global Methane Budget related to natural sources in BU budgets. Here, we further reveal specific uncertainty types and introduce a ranking system for uncertainties in each sector. We find that natural source uncertainty is related particularly to driver data uncertainty in freshwater, vegetation, and coastal/ocean sources, as well as parameter uncertainty in wetland models. Reducing uncertainties, most notably in aquatic and wetland sources will help balance future BU and TD global methane budgets. We suggest a new methane source partitioning over gradients of human disturbance and demonstrate that 76.3% (75.8%–79.4%) or 561 (443–700) Tg CH4 yr−1 of global emissions can be attributed to moderately impacted, man‐made, artificial, or fully anthropogenic sources and 23.7% (20.6%–24.2%) or 174 (115–223) Tg CH4 yr−1 to natural and low impacted methane sources. Finally, we identify current research gaps and provide a plan of action to reduce current uncertainties in the Global Methane Budget.

Immunotherapy has been an advanced and effective approach to treating various types of solid tumors in recent years, and the most successful strategy is immune checkpoint inhibitors (ICIs), which have shown beneficial effects in patients with colorectal cancer (CRC). Drug resistance to ICIs is usually associated with CD8+ T-cells targeting tumor antigens; thus, CD8+ T-cells play an important role in immunotherapy. Unfortunately, Under continuous antigen stimulation, tumor microenvironment(TME), hypoxia and other problems it leads to insufficient infiltration of CD8+ T-cells, low efficacy and mechanism exhaustion, which have become obstacles to immunotherapy. Thus, this article describes the relationship between CRC and the immune system, focuses on the process of CD8+ T-cells production, activation, transport, killing, and exhaustion, and expounds on related mechanisms leading to CD8+ T-cells exhaustion. Finally, this article summarizes the latest strategies and methods in recent years, focusing on improving the infiltration, efficacy, and exhaustion of CD8+ T-cells, which may help to overcome the barriers to immunotherapy.

Lung cancer ranks the top of malignancies that cause cancer-related deaths worldwide. The leaves of Morus alba L are traditional Chinese medicine widely applied in respiratory diseases. Our previous work has demonstrated the anti-lung cancer effect of secondary metabolites of mulberry leaf, but their mechanism of action has still not fully elucidated. We synthesized Moracin N (MAN)-Probe conjugated with alkyne to label lung cancer cells and identified protein targets by chemical proteomic analysis. MAN and its probe exerted similar growth-inhibitory effect on human lung cancer cells. Chemical proteomic results showed that MAN targeted the programmed death ligand 1 (PD-L1) checkpoint pathway and T cell receptor (TCR) signaling pathway, indicating its immune-regulatory function. Cell-free surface plasmon resonance (SPR) results showed the direct interaction of MAN with PD-L1 protein. Molecular docking analysis demonstrated that MAN bound to E158 residue of PD-L1 protein. MAN downregulated the expression levels of PD-L1 in a time- and dose-dependent manner and disrupted the PD-L1/programmed death 1 (PD-1) binding, including other secondary metabolites of mulberry leaves Guangsangon E (GSE) and Chalcomoracin (CMR). Human peripheral blood mononuclear cells (PBMCs) co-cultured with MAN-treated A549 cells, resulting in the increase of CD8+ GZMB+ T cells and the decrease of CD8+ PD-1+ T cells. It suggested that MAN exerts anti-cancer effect through blocking the PD-L1/PD-1 signaling. In vivo, MAN combined with anti-PD-1 antibody significantly inhibited lung cancer development and metastasis, indicating their synergistic effect. Taken together, secondary metabolites of mulberry leaves target the PD-L1/PD-1 signaling, enhance T cell-mediated immunity and inhibit the tumorigenesis of lung cancer. Their modulatory effect on tumor microenvironment makes them able to enhance the therapeutic efficacy of immune checkpoint inhibitors in lung cancer.

Summary: Background: Understanding the impact of CYP2D6 metabolism on paroxetine, a widely used antidepressant, is essential for precision dosing. Methods: We conducted an 8-week, multi-center, single-drug, 2-week wash period prospective cohort study in 921 Chinese Han patients with depressive or anxiety disorders (ChiCTR2000038462). We performed CYP2D6 genotyping (single nucleotide variant and copy number variant) to derive the CYP2D6 activity score and evaluated paroxetine treatment outcomes including steady-state concentration, treatment efficacy, and adverse reaction. CYP2D6 metabolizer status was categorized into poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs), and ultrarapid metabolizers (UMs). The influence of CYP2D6 metabolic phenotype on paroxetine treatment outcomes was examined using multiple regression analysis and cross-ethnic meta-analysis. The therapeutic reference range of paroxetine was estimated by receiver operating characteristic (ROC) analyses. Findings: After adjusting for demographic factors, the steady-state concentrations of paroxetine in PMs, IMs, and UMs were 2.50, 1.12, and 0.39 times that of EMs, with PM and UM effects being statistically significant (multiple linear regression, P = 0.03 and P = 0.04). Sex and ethnicity influenced the comparison between IMs and EMs. Moreover, poor efficacy of paroxetine was associated with UM, and a higher risk of developing adverse reactions was associated with lower CYP2D6 activity score. Lastly, cross-ethnic meta-analysis suggested dose adjustments for PMs, IMs, EMs, and UMs in the East Asian population to be 35%, 40%, 143%, and 241% of the manufacturer's recommended dose, and 62%, 68%, 131%, and 159% in the non-East Asian population. Interpretation: Our findings advocate for precision dosing based on the CYP2D6 metabolic phenotype, with sex and ethnicity being crucial considerations in this approach. Funding: National Natural Science Foundation of China; Academy of Medical Sciences Research Unit.

Esophageal carcinoma is a prevalent gastrointestinal malignancy worldwide. Effective treatment agents and procedures are crucial in the current global health problem. Kumatakenin (KM), a key ingredient in traditional Chinese medicinal cloves and Alpinia purpurata, has been widely explored for its therapeutic properties. However, Kumatakenin's oesophageal cancer inhibitory actions and pharmacological molecular mechanisms must be fully explored. The study found that knowledge management (KM) deactivated the E3 ubiquitin-protein ligase TRIM65 to decrease esophageal cancer cell proliferation and delay tumor development. The dosage-dependent suppression of esophageal cancer cell migration and invasion by KM was significant. Potassium monoxide (KM) reduced esophageal cancer growth in a well-established xenograft mouse model. High-throughput RNA sequencing and stable isotope labelling with amino acids in cell cultures (SILAC) were used to identify KM-induced gene dysregulation in esophageal cancer cells. TRIM65, a ubiquitinating enzyme, is essential to esophageal cancer growth. In addition, TRIM65 and FASN are linked in this syndrome. In addition, KM treatments reduced TRIM65 expression, FASN stability, and expression in esophageal cancer cells. Validating these findings in animal model tumor tissues confirmed them. The mechanistic investigation showed that TRIM65 directly connects with FASN in cancer cells, stabilizing FASN via K63-linked polyubiquitination. KM therapy disrupted interaction and stabilization mechanisms, according to this study. The enhanced stability of FASN in esophageal cancer cells enabled lipid synthesis and deposition. This enhanced cancer cell growth and tumor formation. Our findings show that upregulating TRIM65 increases cancer cell proliferation, migration, and invasion and reduces KM's suppressive effects on esophageal cancer. This study shows that TRIM65 inhibition is essential for KM's antineoplastic activities. The results of our study strongly suggest that knowledge management (KM) may treat esophageal cancer. This result comes from suppressing TRIM65-FASN signaling.

A 43-year-old woman with a history of uterine fibroids, anemia, and deep vein thrombosis presented with a chief symptom of prolapse of tumor from the perineum, complicated by infection. The case was further complicated by bilateral pulmonary multiple embolism, deep vein thrombosis, acute cardiac insufficiency, acute renal insufficiency, and shock. The patient was treated with preoperative placement of an inferior vena cava filter, open hysterectomy, and perioperative anticoagulation with low-molecular-weight heparin. She smoothly navigated the perioperative period and recovered completely.

Abstract BackgroundSome common modified vascular risk factors remain poorly controlled among stroke survivors, and educational programs may help improve these conditions. ObjectiveThis study aimed to evaluate the effect of a planned web-based educational intervention based on the health belief model (HBM) in promoting secondary prevention among patients with ischemic stroke. MethodsAn evaluation-blinded quasi-experimental trial with a historical control group was conducted. Patients admitted from March to June 2020 were assigned to the historical control group, and patients admitted from July to October 2020 were assigned to the intervention group. The control group received routine health management. The intervention group received 6 additional sessions based on the HBM via Tencent Meeting, an audio and video conferencing application, within 3 months after discharge. Sessions were held every 2 weeks, with each session lasting approximately 40 minutes. These sessions were conducted in small groups, with about 8 to 10 people in each group. The primary outcomes were changes in blood pressure (BP), low-density lipoprotein cholesterol (LDL-C), hemoglobin A1c1c ResultsIn total, 315 patients experiencing their first-ever stroke were analyzed. More patients in the intervention group had controlled BP (41.9% vs 28.4%; adjusted odds ratio [aOR] 1.93; PP1cPβPβP1cβPP ConclusionsA web-based education program based on the HBM may be more effective than current methods used to educate patients having strokes on optimal vascular risk factors and medication adherence.