Deep learning algorithms for melanoma detection using dermoscopic images: A systematic review and meta-analysis.

BACKGROUND: Melanoma is a serious risk to human health and early identification is vital for treatment success. Deep learning (DL) has the potential to detect cancer using imaging technologies and many studies provide evidence that DL algorithms can achieve high accuracy in melanoma diagnostics. OBJECTIVES: To critically assess different DL performances in diagnosing melanoma using dermatoscopic images and discuss the relationship between dermatologists and DL. METHODS: Ovid-Medline, Embase, IEEE Xplore, and the Cochrane Library were systematically searched from inception until 7th December 2021. Studies that reported diagnostic DL model performances in detecting melanoma using dermatoscopic images were included if they had specific outcomes and histopathologic confirmation. Binary diagnostic accuracy data and contingency tables were extracted to analyze outcomes of interest, which included sensitivity (SEN), specificity (SPE), and area under the curve (AUC). Subgroup analyses were performed according to human-machine comparison and cooperation. The study was registered in PROSPERO, CRD42022367824. RESULTS: 2309 records were initially retrieved, of which 37 studies met our inclusion criteria, and 27 provided sufficient data for meta-analytical synthesis. The pooled SEN was 82 % (range 77-86), SPE was 87 % (range 84-90), with an AUC of 0.92 (range 0.89-0.94). Human-machine comparison had pooled AUCs of 0.87 (0.84-0.90) and 0.83 (0.79-0.86) for DL and dermatologists, respectively. Pooled AUCs were 0.90 (0.87-0.93), 0.80 (0.76-0.83), and 0.88 (0.85-0.91) for DL, and junior and senior dermatologists, respectively. Analyses of human-machine cooperation were 0.88 (0.85-0.91) for DL, 0.76 (0.72-0.79) for unassisted, and 0.87 (0.84-0.90) for DL-assisted dermatologists. CONCLUSIONS: Evidence suggests that DL algorithms are as accurate as senior dermatologists in melanoma diagnostics. Therefore, DL could be used to support dermatologists in diagnostic decision-making. Although, further high-quality, large-scale multicenter studies are required to address the specific challenges associated with medical AI-based diagnostics.

Distribution and diagnostic value of single and multiple high-risk HPV infections in detection of cervical intraepithelial neoplasia: A retrospective multicenter study in China.

The risk associated with single and multiple human papillomavirus (HPV) infections in cervical intraepithelial neoplasia (CIN) remains uncertain. This study aims to explore the distribution and diagnostic significance of the number of high-risk HPV (hr-HPV) infections in detecting CIN, addressing a crucial gap in our understanding. This comprehensive multicenter, retrospective study meticulously analyzed the distribution of single and multiple hr-HPV, the risk of CIN2+, the relationship with CIN, and the impact on the diagnostic performance of colposcopy using demographic information, clinical histories, and tissue samples. The composition of a single infection was predominantly HPV16, 52, 58, 18, and 51, while HPV16 and 33 were identified as the primary causes of CIN2+. The primary instances of dual infection were mainly observed in combinations such as HPV16/18, HPV16/52, and HPV16/58, while HPV16/33 was identified as the primary cause of CIN2+. The incidence of hr-HPV infections shows a dose-response relationship with the risk of CIN (p for trend <0.001). Compared to single hr-HPV, multiple hr-HPV infections were associated with increased risks of CIN1 (1.44, 95% confidence interval [CI]: 1.20-1.72), CIN2 (1.70, 95% CI: 1.38-2.09), and CIN3 (1.08, 95% CI: 0.86-1.37). The colposcopy-based specificity of single hr-HPV (93.4, 95% CI: 92.4-94.4) and multiple hr-HPV (92.9, 95% CI: 90.8-94.6) was significantly lower than negative (97.9, 95% CI: 97.0-98.5) in detecting high-grade squamous intraepithelial lesion or worse (HSIL+). However, the sensitivity of single hr-HPV (73.5, 95% CI: 70.8-76.0) and multiple hr-HPV (71.8, 95% CI: 67.0-76.2) was higher than negative (62.0, 95% CI: 51.0-71.9) in detecting HSIL+. We found that multiple hr-HPV infections increase the risk of developing CIN lesions compared to a single infection. Colposcopy for HSIL+ detection showed high sensitivity and low specificity for hr-HPV infection. Apart from HPV16, this study also found that HPV33 is a major pathogenic genotype.

Size-dependent influences of nano- and micro-plastics exposure on feeding, antioxidant systems, and organic sulfur compounds in ciliate Uronema marinum.

Protozoa play a pivotal role in the microbial cycle, and ciliated protozoan grazing habits are associated with dimethyl sulfide (DMS) cycle. Many studies have explored the impacts of nanoplastics (NPs) and microplastics (MPs) on ecotoxicological effects of ciliates. However, limited research exists on NPs and MPs influences on the production of organic sulfur compounds. The impact of NPs and MPs on the production of dimethyl sulfoxide (DMSO) and carbonyl sulfide (COS) remains unclear. Therefore, we examined the impacts of three concentrations (1 × 105, 5 × 105, and 1 × 106 items/mL) of polystyrene (PS) NPs (50 nm) and MPs (1 and 5 µm) on the ecotoxicology and DMS/dimethylsulfoniopropionate (DMSP)/DMSO/COS production in the ciliate Uronema marinum. NPs and MPs exposure were found to reduce the abundance, growth rate, volume, and biomass of U. marinum. Additionally, NPs and MPs increased the superoxide anion radical (O2˙─) production rates and malondialdehyde (MDA) contents (24 h), leading to a decline in glutathione (GSH) content and an ascend in superoxide dismutase (SOD) activity to mitigate the effects of reactive oxygen species (ROS). Exposure to PS NPs and MPs decreased the ingestion rates of algae by 7.5-14.4%, resulting in decreases in DMS production by 56.8-85.4%, with no significant impact on DMSO production. The results suggest a distinct pathway for the production of DMSO or COS compared to DMS. These findings help us to understand the NPs and MPs impacts on the marine ecosystem and organic sulfur compound yield, potentially influencing the global climate.

Esculetin facilitates post-stroke rehabilitation by inhibiting CKLF1-mediated neutrophil infiltration.

Esculetin (ESC) is a coumarin-derived phytochemical prevalent in traditional Chinese medicine that exhibits anti-acute ischemic stroke activities. Our previous studies demonstrate that CKLF1 is a potential anti-stroke target for coumarin-derived compound. In this study we investigated whether CKLF1 was involved in the neuroprotective effects of ESC against photothrombotic stroke in mice. The mice were treated with ESC (20, 40 or 80 mg·kg-1·d-1, i.g.) for two weeks. The therapeutic effect of ESC was assessed using MRI, neurological function evaluation, and a range of behavioral tests on D1, 3, 7 and 14 of ESC administration. We showed that oral administration of ESC dose-dependently reduced the cerebral infarction volume within one week after stroke, improved behavioral performance, and alleviated neuropathological damage within two weeks. Functional MRI revealed that ESC significantly enhanced the abnormal low-frequency fluctuation (ALFF) value of the motor cortex and promoted functional connectivity between the supplementary motor area (SMA) and multiple brain regions. We demonstrated that ESC significantly reduced the protein levels of CKLF1 and CCR5, as well as the CKLF1/CCR5 protein complex in the peri-infarcted area. We showed that ESC (0.1-10 µM) dose-dependently blocked CKLF1-induced chemotactic movement of neutrophils in the Transwell assay, reducing the interaction of CKLF1/CCR5 on the surface of neutrophils, thereby reducing neutrophil infiltration, and decreasing the expression of ICAM-1, VCAM-1 and MMP-9 in the peri-infarct tissue. Knockout of CKLF1 reduced brain infarction volume and motor dysfunction after stroke but also negated the anti-stroke efficacy and neutrophil infiltration of ESC. These results suggest that the efficacy of ESC in promoting post-stroke neural repair depends on its inhibition on CKLF1-mediated neutrophil infiltration, which offering novel perspectives for elucidating the therapeutic properties of coumarins.

Unveiling Commonalities and Differences in Genetic Regulations via Two-Way Fusion.

Understanding the genetic regulation, for example, gene expressions (GEs) by copy number variations and methylations, is crucial to uncover the development and progression of complex diseases. Advancing from early studies that are mostly focused on homogeneous groups of patients, some recent studies have shifted their focus toward different patient groups, explored their commonalities and differences, and led to insightful findings. However, the analysis can be very challenging with one GE possibly regulated by multiple regulators and one regulator potentially regulating the expressions of multiple genes, leading to two distinct types of commonalities/differences in the patterns of genetic regulation. In addition, the high dimensionality of both sides of regulation poses challenges to computation. In this study, we develop a two-way fusion integrative analysis approach, which innovatively applies two fusion penalties to simultaneously identify commonalities/differences in the regulated pattern of GEs and regulating pattern of regulators, and adopt a Huber loss function to accommodate the possible data contamination. Moreover, a simple yet efficient iterative optimization algorithm is developed, which does not need to introduce any auxiliary variables and extra tuning parameters and is guaranteed to converge to a globally optimal solution. The advantages of the proposed approach are demonstrated in extensive simulations. The analysis of The Cancer Genome Atlas data on melanoma and lung cancer leads to interesting findings and satisfactory prediction performance.

Distributed Drive Electric Vehicle Handling Stability Coordination Control Framework Based on Adaptive Model Predictive Control.

Distributed drive electric vehicles improve steering response and enhance overall vehicle stability by independently controlling each motor. This paper introduces a control framework based on Adaptive Model Predictive Control (AMPC) for coordinating handling stability, consisting of three layers: the dynamic supervision layer, online optimization layer, and low-level control layer. The dynamic supervision layer considers the yaw rate and maneuverability limits when establishing the ß-ß˙ phase plane stability boundary and designs variable weight factors based on this stability boundary. The online optimization layer constructs the target weight-adaptive AMPC strategy, which can adjust the control weights for maneuverability and lateral stability in real time based on the variable weight factors provided by the dynamic supervision layer. The low-level control layer precisely allocates the driver's requested driving force and additional yaw moment by using torque distribution error and tire utilization as the cost function. Finally, experiments are conducted on a Simulink-CarSim co-simulation platform to assess the performance of AMPC. Simulation results show that, compared to the traditional MPC strategy, this control strategy not only enhances maneuverability under normal conditions but also improves lateral stability control under extreme conditions.

MRG15 aggravates sepsis-related liver injury by promoting PCSK9 synthesis and secretion.

OBJECTIVE: Disorders of lipid oxidation play an important role in organ damage, and lipid metabolites are associated with inflammation and coagulation dysfunction in sepsis. However, the specific molecular mechanism by which lipid metabolism-related proteins regulate sepsis is still unclear. The aim of this study is to investigate the role of mortality factor 4-like protein 1 (MORF4L1, also called MRG15), a hepatic lipid metabolism related gene, in sepsis-induced liver injury. METHODS: In the mouse sepsis models established by cecal ligation and puncture (CLP) and lipopolysaccharide (LPS), the impact of pretreatment with the MRG15 inhibitor argatroban on sepsis-related liver injury was investigated. In the LPS-induced hepatocyte sepsis cell model, the effects of MRG15 overexpression or knockdown on hepatic inflammation and lipid metabolism were studied. Additionally, in a co-culture system of hepatocytes and macrophages, the influence of MRG15 knockdown in hepatocytes on the synthesis and secretion of inflammation-related protein PCSK9 as well as its effect on macrophage activation were examined. RESULTS: Studies have shown that MRG15 expression was increased in septicemia mice and positively correlated with lipid metabolism and inflammation. However, knockdown of MRG15 ameliorates sepsis-induced hepatocyte injury. Increased MRG15 in LPS-stimulated hepatocytes promotes PCSK9 synthesis and secretion, which induces macrophage M1 polarization and exacerbates the inflammatory response. Agatroban, an inhibitor of MRG15, ameliorates sepsis-induced liver injury in mice by inhibiting MRG15-induced lipid metabolism disorders and inflammatory responses. CONCLUSIONS: In sepsis, increased MRG15 expression in hepatocytes leads to disturbed hepatic lipid metabolism and induces macrophage M1 polarization by secreting PCSK9, ultimately exacerbating liver injury.

Impacts of nano- and micro-plastics exposure on zooplankton grazing, bacterial communities, and dimethylated sulfur compounds production in the microcosms.

Dimethyl sulfide (DMS) is a prevalent volatile organic sulfur compound relevant to the global climate. Ecotoxicological effects of nano- and microplastics (NPs and MPs) on phytoplankton, zooplankton, and bacteria have been investigated by numerous studies. Yet, the influences of NPs/MPs on dimethylated sulfur compounds remains understudied. Herein, we investigated the impacts of polystyrene (PS) NPs/MPs (80 nm, 1 µm, and 10 µm) on zooplankton grazing, chlorophyll a (Chl a) concentration, bacterial community, dimethylsulfoniopropionate (DMSP), and DMS production in the microcosms. Our findings revealed that rotifer grazing increased the production of DMS in the absence of NPs/MPs but did not promote DMS production when exposed to NPs/MPs. The ingestion rates of the rotifer and copepod exposed to NPs/MPs at high concentrations were significantly reduced. NPs/MPs exposure significantly decreased DMS levels in the treatments with rotifers compared to the animal controls. In the bacterial microcosms, smaller NPs/MPs sizes were more detrimental to Chl a concentrations compared to larger sizes. The study revealed a stimulatory effect on Chl a concentrations, DMSPd concentrations, and bacterial abundances when exposed to 10 µm MP with low concentrations. The effects of NPs/MPs on DMS concentrations were both dose- and size-dependent, with NPs showing greater toxicity compared to larger MPs. NPs/MPs led to changes in bacterial community compositions, dependent on both dosage and size. NPs caused a notable decrease in the alpha diversities and richness of bacteria compared to MPs. These results provide insights into the influences of NPs/MPs on food webs, and subsequently organic sulfur compounds cycles.

Genome composition-based deep learning predicts oncogenic potential of HPVs.

Human papillomaviruses (HPVs) account for more than 30% of cancer cases, with definite identification of the oncogenic role of viral E6 and E7 genes. However, the identification of high-risk HPV genotypes has largely relied on lagged biological exploration and clinical observation, with types unclassified and oncogenicity unknown for many HPVs. In the present study, we retrieved and cleaned HPV sequence records with high quality and analyzed their genomic compositional traits of dinucleotide (DNT) and DNT representation (DCR) to overview the distribution difference among various types of HPVs. Then, a deep learning model was built to predict the oncogenic potential of all HPVs based on E6 and E7 genes. Our results showed that the main three groups of Alpha, Beta, and Gamma HPVs were clearly separated between/among types in the DCR trait for either E6 or E7 coding sequence (CDS) and were clustered within the same group. Moreover, the DCR data of either E6 or E7 were learnable with a convolutional neural network (CNN) model. Either CNN classifier predicted accurately the oncogenicity label of high and low oncogenic HPVs. In summary, the compositional traits of HPV oncogenicity-related genes E6 and E7 were much different between the high and low oncogenic HPVs, and the compositional trait of the DCR-based deep learning classifier predicted the oncogenic phenotype accurately of HPVs. The trained predictor in this study will facilitate the identification of HPV oncogenicity, particularly for those HPVs without clear genotype or phenotype.

Bithieno[3,4-c]pyrrole-4,6-dione-Based Wide-Bandgap Donor Polymers for Efficient Polymer Solar Cells.

The polymer solar cells (PSCs) have garnered substantial interest owing to their lightweight, cost-effectiveness, and flexibility, making them ideal for large-scale roll-to-roll manufacturing. In this study, two wide-bandgap (WBG) donor polymers, PFBiTPD and PClBiTPD, utilizing bithieno[3,4-c]pyrrole-4,6-dione (BiTPD) as the electron-accepting unit and fluorinated/chlorinated benzo[1,2-b:4,5-b']dithiophene (BDT) as the electron-donating moiety are designed and synthesized. The polymers demonstrated large optical bandgaps (exceeding 1.80 eV) and are blended with ITIC-4F to form the active layers in PSCs. The PFBiTPD-based devices showed a well-dispersed fibrillar network, facilitating efficient charge generation and transport. Thus, these devices attained a power conversion efficiency (PCE) of 8.60%, featuring a fill factor (FF) of 62.89%, an open-circuit voltage (Voc) of 0.88 V and a short-circuit current density (Jsc) of 15.54 mA cm-2. In contrast, PClBiTPD-based devices displayed lower performance due to less favorable morphology. The study underscores the importance of polymer design and morphology control in optimizing the photovoltaic performance of PSCs.

AIE-YOLO: Effective object detection method in extreme driving scenarios via adaptive image enhancement.

The widespread research and implementation of visual object detection technology have significantly transformed the autonomous driving industry. Autonomous driving relies heavily on visual sensors to perceive and analyze the environment. However, under extreme weather conditions, such as heavy rain, fog, or low light, these sensors may encounter disruptions, resulting in decreased image quality and reduced detection accuracy, thereby increasing the risk for autonomous driving. To address these challenges, we propose adaptive image enhancement (AIE)-YOLO, a novel object detection method to enhance road object detection accuracy under extreme weather conditions. To tackle the issue of image quality degradation in extreme weather, we designed an improved adaptive image enhancement module. This module dynamically adjusts the pixel features of road images based on different scene conditions, thereby enhancing object visibility and suppressing irrelevant background interference. Additionally, we introduce a spatial feature extraction module to adaptively enhance the model's spatial modeling capability under complex backgrounds. Furthermore, a channel feature extraction module is designed to adaptively enhance the model's representation and generalization abilities. Due to the difficulty in acquiring real-world data for various extreme weather conditions, we constructed a novel benchmark dataset named extreme weather simulation-rare object dataset. This dataset comprises ten types of simulated extreme weather scenarios and is built upon a publicly available rare object detection dataset. Extensive experiments conducted on the extreme weather simulation-rare object dataset demonstrate that AIE-YOLO outperforms existing state-of-the-art methods, achieving excellent detection performance under extreme weather conditions.

Mutual exclusivity and co-occurrence patterns of immune checkpoints indicate NKG2A relates to anti-PD-1 resistance in gastric cancer.

BACKGROUND: An increasing number of clinical studies have begun to explore combination strategies with immune checkpoint inhibitors, aiming to present new opportunities for overcoming anti-PD-1 treatment resistance in gastric cancer. Unfortunately, the exploration of certain immune checkpoint inhibitor combination strategies has yielded suboptimal results. Therefore, it is necessary to comprehensively analyze the expression patterns of immune checkpoints and identify optimal combination regimens of anti-PD-1 inhibitors with other immune checkpoint inhibitors. METHODS: Leveraging single-cell RNA sequencing (scRNA-seq) and multivariate linear regression interaction models, we dissected the immune checkpoint expression characteristics of CD8+ T cells in gastric cancer and the immune checkpoint expression pattern (ICEP) mediating anti-PD-1 treatment resistance. Furthermore, we employed transcription factor analysis and CellOracle to explore the transcriptional regulatory mechanisms governing CD8+ T cell differentiation fates. Finally, we utilized Nichenet and spatial transcriptomic analysis to investigate the spatial expression patterns of immune checkpoints. RESULTS: Interaction analysis indicated that, among the known immune checkpoints, co-expression of NKG2A and PD-1 might exert a more profound inhibitory effect on the proliferative capacity of CD8+ T cells. The co-expression analysis revealed differential co-expression pattern of PD-1 and NKG2A, defined as ICEP1 (CD8+ T cells co-expressing PD-1, CTLA-4, TIGIT, LAG-3 or CD38) and ICEP2 (CD8+ T cells solely expressing NKG2A or co-expressing with other immune checkpoints), reflecting the co-occurrence pattern of PD-1 and the mutual exclusivity of NKG2A. Further, these two ICEP CD8+ T cell subsets represented distinct CD8+ T cell differentiation fates governed by MSC and RUNX3. Notably, ICEP2 CD8+ T cells were associated with anti-PD-1 therapy resistance in gastric cancer. This phenomenon may be attributed to the recruitment of LGMN+ macrophages mediated by the CXCL16-CXCR6 signaling pathway. CONCLUSION: This study unveiled two distinct ICEPs and the mutually exclusivity and co-occurrence characteristics of CD8+ T cells in gastric cancer. The ICEP2 CD8+ T cell subset, highly expressed in gastric cancer patients resistant to anti-PD-1 therapy, may be recruited by LGMN+ macrophages through CXCL16-CXCR6 axis. These findings provide evidence for NKG2A as a novel immunotherapeutic target in gastric cancer and offer new insights into combination strategies for immune checkpoint inhibitors in gastric cancer.

Association between glucose levels of children with type 1 diabetes and parental economic status in mobile health application.

BACKGROUND: The glycemic control of children with type 1 diabetes (T1D) may be influenced by the economic status of their parents. AIM: To investigate the association between parental economic status and blood glucose levels of children with T1D using a mobile health application. METHODS: Data from children with T1D in China's largest T1D online community, Tang-TangQuan®. Blood glucose levels were uploaded every three months and parental economic status was evaluated based on annual household income. Children were divided into three groups: Low-income (< 30000 Yuan), middle-income (30000-100000 Yuan), and high-income (> 100000 yuan) (1 Yuan = 0.145 United States Dollar approximately). Blood glucose levels were compared among the groups and associations were explored using Spearman's correlation analysis and multivariable logistic regression. RESULTS: From September 2015 to August 2022, 1406 eligible children with T1D were included (779 female, 55.4%). Median age was 8.1 years (Q1-Q3: 4.6-11.6) and duration of T1D was 0.06 years (0.02-0.44). Participants were divided into three groups: Low-income (n = 320), middle-income (n = 724), and high-income (n = 362). Baseline hemoglobin A1c (HbA1c) levels were comparable among the three groups (P = 0.072). However, at month 36, the low-income group had the highest HbA1c levels (P = 0.036). Within three years after registration, glucose levels increased significantly in the low-income group but not in the middle-income and high-income groups. Parental economic status was negatively correlated with pre-dinner glucose (r = -0.272, P = 0.012). After adjustment for confounders, parental economic status remained a significant factor related to pre-dinner glucose levels (odds ratio = 13.02, 95%CI: 1.99 to 126.05, P = 0.002). CONCLUSION: The blood glucose levels of children with T1D were negatively associated with parental economic status. It is suggested that parental economic status should be taken into consideration in the management of T1D for children.

Graphene Intermediate Layer for Robust and Spectrum-Extended Cu Photocathode Activated with Cs and O.

Developing an effective method to stably enhance the quantum efficiency (QE) and extend the photoemission threshold of Cu photocathodes beyond the ultraviolet region could benefit the photoinjector for ultrafast electron source applications. The implementation of a 2D material protective layer is considered a promising approach to extending the operating lifetime of photocathodes. We propose that graphene can serve as an intermediate layer at the interface between photocathode material and low-work-function coating. The role of oxygen in the Cs/O activation process on the Cu surface is altered by the graphene interlayer. Besides, the few-layer graphene (FLG) surface could be more likely to induce the formation of Cs2O. Thus, the graphene-Cu composite photocathode can achieve an ultralow surface work function of down to 0.878 eV through Cs/O activation. The photoemission performance of the composite cathode with a FLG interlayer is significantly enhanced. The photocathode has an extended spectral response to the near-infrared region and a higher QE. At 350 nm, its QE is more than twice that of the cesiated bare Cu, reaching 0.247%. After degradation, the graphene-Cu cathode can be fully restored by reactivation, with remarkably enhanced stability. In addition, the composite cathode can be operated reliably under a poor vacuum pressure of over 4 × 10-6 Pa. This study validates a new method for incorporating 2D materials into photocathodes, offering novel approaches to explore robust and spectrum-extended photocathodes.

Simultaneous carbon, nitrogen and phosphorus removal in sequencing batch membrane aerated biofilm reactor with biofilm thickness control via air scouring aided by computational fluid dynamics.

Membrane aerated biofilm reactor (MABR) is challenged by biofilm thickness control and phosphorus removal. Air scouring aided by computational fluid dynamics (CFD) was employed to detach outer biofilm in sequencing batch MABR treating low C/N wastewater. Biofilm with 177-285 µm thickness in cycle 5-15 achieved over 85 % chemical oxygen demand (COD) and total inorganic nitrogen (TIN) removals at loading rate of 13.2 gCOD/m2/d and 2.64 gNH4+-N/m2/d. Biofilm rheology measurements in cycle 10-25 showed yield stress against detachment of 2.8-7.4 Pa, which were equal to CFD calculated shear stresses under air scouring flowrate of 3-9 L/min. Air scouring reduced effluent NH4+-N by 10 % and biofilm thickness by 78 µm. Intermittent aeration (4h off, 19.5h on) and air scouring (3 L/min, 30 s before settling) in one cycle achieved COD removal over 90 %, TIN and PO43--P removals over 80 %, showing great potential for simultaneous carbon, nitrogen and phosphorus removals.

Multi-omic Analyses Shed Light on The Genetic Control of High-altitude Adaptation in Sheep.

Sheep were domesticated in the Fertile Crescent and then spread globally, where they have been encountering various environmental conditions. The Tibetan sheep has adapted to high altitudes on the Qinghai-Tibet Plateau over the past 3000 years. To explore genomic variants associated with high-altitude adaptation in Tibetan sheep, we analyzed Illumina short-reads of 994 whole genomes representing ∼ 60 sheep breeds/populations at varied altitudes, PacBio High fidelity (HiFi) reads of 13 breeds, and 96 transcriptomes from 12 sheep organs. Association testing between the inhabited altitudes and 34,298,967 variants was conducted to investigate the genetic architecture of altitude adaptation. Highly accurate HiFi reads were used to complement the current ovine reference assembly at the most significantly associated ß-globin locus and to validate the presence of two haplotypes A and B among 13 sheep breeds. The haplotype A carried two homologous gene clusters: (1) HBE1, HBE2, HBB-like, and HBBC, and (2) HBE1-like, HBE2-like, HBB-like, and HBB; while the haplotype B lacked the first cluster. The high-altitude sheep showed highly frequent or nearly fixed haplotype A, while the low-altitude sheep dominated by haplotype B. We further demonstrated that sheep with haplotype A had an increased hemoglobin-O2 affinity compared with those carrying haplotype B. Another highly associated genomic region contained the EGLN1 gene which showed varied expression between high-altitude and low-altitude sheep. Our results provide evidence that the rapid adaptive evolution of advantageous alleles play an important role in facilitating the environmental adaptation of Tibetan sheep.

Rising atmospheric carbon dioxide concentrations increase gaps of rice yields between low- and middle-to-high-income countries.

The rising carbon dioxide concentrations are expected to increase future rice yields. However, variations in the CO2 fertilization effect (CFE) between rice subspecies and the influence of concurrent global warming introduce uncertainty in future global rice yield projections. Here we conducted a meta-analysis of rising carbon dioxide field experiments and employed crop modelling to assess future global rice yields for the top 14 rice producing countries. We found a robust parabolic relationship between rice CFE and temperature, with significant variations between rice subspecies. Our projections indicate that global rice production in the 2050s is expected to increase by 50.32 million tonnes (7.6%) due to CFE compared with historical production. Because low-income countries will experience higher temperatures, the gaps (difference of Δyield) between middle-to-high-income and low-income countries are projected to widen from the 2030s to the 2090s under elevated carbon dioxide. These findings underscore the critical role of CFE and emphasize the necessity to increase investments in research and technology for rice producing systems in low-income countries.

Amino-Functionalized Metal-Organic Frameworks Featuring Ultra-Strong Ethane Nano-Traps for Efficient C2H6/C2H4 Separation.

Developing high-performance porous materials to separate ethane from ethylene is an important but challenging task in the chemical industry, given their similar sizes and physicochemical properties. Herein, a new type of ultra-strong C2H6 nano-trap, CuIn(3-ain)4 is presented, which utilizes multiple guest-host interactions to efficiently capture C2H6 molecules and separate mixtures of C2H6 and C2H4. The ultra-strong C2H6 nano-trap exhibits the high C2H6 (2.38 mmol g-1) uptake at 6.25 kPa and 298 K and demonstrates a remarkable selectivity of 3.42 for C2H6/C2H4 (10:90). Additionally, equimolar C2H6/C2H4 exhibited a superior high separation potential ∆Q (2286 mmol L-1) at 298 K. Kinetic adsorption tests demonstrated that CuIn(3-ain)4 has a high adsorption rate for C2H6, establishing it as a new benchmark material for the capture of C2H6 and the separation of C2H6/C2H4. Notably, this exceptional performance is maintained even at a higher temperature of 333 K, a phenomenon not observed before. Theoretical simulations and single-crystal X-ray diffraction provide critical insights into how selective adsorption properties can be tuned by manipulating pore dimensions and geometry. The excellent separation performance of CuIn(3-ain)4 has been confirmed through breakthrough experiments for C2H6/C2H4 gas mixtures.

Comparison of ultrasonic diagnosis of cesarean scar defects at different timepoints following cesarean section.

Background: Cesarean scar defect (CSD) is a potential complication following cesarean section (CS), which has significant clinical implications, and is usually clinically diagnosed by ultrasound. However, the optimal timing for ultrasound diagnosis of CSD after CS has not been well established. This study aimed to evaluate the appropriate time for the diagnosis of CSD after CS by ultrasonography. Methods: The prospective study involved 120 women who delivered by elective CS with single birth and term birth from January 2021 to June 2022. Sample enrollment was consecutive in the study. Each woman underwent 3 ultrasound examinations for CSD diagnosis at 6 weeks, 6 months, and 12 months postpartum according to a modified Delphi method. The ultrasound indicators about the incision situation were recorded and statistically analyzed. Paired 4-fold table chi-square test was used to evaluate the consistency between the 3 diagnoses. The diagnostic sensitivity and specificity were calculated using a 4-cell table. According to whether the diagnosis was consistent to that at 6 or 12 months, the 120 cases at week 6 were separated into a consistent group and inconsistent group for statistical evaluation of the ultrasound indicators. Additionally, the menstrual duration of the included women was also recorded to analyze the correlation to ultrasound indicators of CSD at 6 months postpartum using the Person correlation coefficient. Results: The included 120 women were divided into normal (3-7 days, n=52) and prolonged menstrual period (>7 days, n=68) groups. The 2 groups had no statistical differences in age, body mass index (BMI), gestational week of delivery, assisted reproduction rates, or postpartum complications. Among the 120 women, 100, 66, and 61 women were diagnosed as CSD at 6 weeks, 6 months, and 12 months postpartum, respectively. The results indicated that the diagnostic results of 6 weeks were inconsistent with those of 6 or 12 months postpartum, but the last 2 diagnostic results were consistent. The diagnostic sensitivity of 6 months was 100% and the specificity was 91.53% [95% confidence interval (CI): 85.84-95.26%]. Further, significant differences were found in depth of the defect, and the thickness (T) and ratio of residual muscle between the inconsistent group and the consistent group at 6 weeks. The patients could be considered self-recovered from CSD at 6 months when the defect depth was equal to or less than 4.04±0.82 mm at 6 weeks after CS. Additionally, in the CSD group at 6 months, the length (r=0.828, P<0.001), depth (r=0.784, P<0.001), width (r=0.787, P<0.001) of the defect, the T (r=0.831, P<0.001) and ratio of residual muscle (r=0.821, P<0.001) were strongly correlated with menstrual duration. Conclusions: CSD evaluation at week 6 after CS may cause misdiagnosis or overdiagnosis. The diagnosis of CSD was suggested to be made following 6 months or longer postpartum.

Evaluation of the efficacy of intrauterine treatments of twin-to-twin transfusion syndrome using myocardial performance index.

Background: Prognosis of twin-to-twin transfusion syndrome (TTTS) varies depending on the Quintero stage and fetal cardiac function. The purpose of our study was to evaluate fetal cardiac function before and after different intrauterine treatments of TTTS through myocardial performance index (MPI). Methods: In this retrospective study, data were collected from August 2016 to December 2022. Totals of 68 cases of TTTS and 68 monochorionic diamniotic (MCDA) twins without TTTS were included. MPI was collected and compared between TTTS and MCDA twins without TTTS before intrauterine treatments. TTTS cases were divided into 3 groups according to different intrauterine treatments: (I) amnioreduction (34 cases), (II) fetoscopic laser photocoagulation (FLPC; 20 cases), and (III) selective reduction (14 cases). The MPI of the left ventricle (LV) and right ventricle (RV) in each surviving fetus were measured 48 hours before and after treatments by pulse Doppler ultrasound. One-way analysis of variance (ANOVA) was employed to assess whether there were statistical differences in LV-MPI and RV-MPI among the donors, recipients, and the control group. Paired t-test analysis was used to compare whether there were differences in MPI before and after intrauterine treatments. Results: The MPIs of the LV and RV in the recipients were significantly higher than those in the MCDA twins without TTTS (P<0.05). After the amnioreduction treatment of TTTS, no significant differences were observed in the MPI of either the LV or the RV before and after treatment. At 48 hours after FLPC treatment, the value of the LV-MPI in donors was 0.25±0.08, and the value of the RV-MPI in recipients was 0.58±0.17. Both of them were significantly lower than those before the treatment (P<0.05). In the selective reduction group, the value of the RV-MPI in surviving recipients significantly decreased compared to that before treatment (P<0.05). Conclusions: MPI is an effective indicator to evaluate fetal cardiac function of TTTS and assess the efficacy of intrauterine treatments of TTTS.