Adaptive evolution of the enigmatic Takakia now facing climate change in Tibet.

The most extreme environments are the most vulnerable to transformation under a rapidly changing climate. These ecosystems harbor some of the most specialized species, which will likely suffer the highest extinction rates. We document the steepest temperature increase (2010-2021) on record at altitudes of above 4,000 m, triggering a decline of the relictual and highly adapted moss Takakia lepidozioides. Its de-novo-sequenced genome with 27,467 protein-coding genes includes distinct adaptations to abiotic stresses and comprises the largest number of fast-evolving genes under positive selection. The uplift of the study site in the last 65 million years has resulted in life-threatening UV-B radiation and drastically reduced temperatures, and we detected several of the molecular adaptations of Takakia to these environmental changes. Surprisingly, specific morphological features likely occurred earlier than 165 mya in much warmer environments. Following nearly 400 million years of evolution and resilience, this species is now facing extinction.

Long-range order enabled stability in quantum dot light-emitting diodes.

Light-emitting diodes (LEDs) based on perovskite quantum dots (QDs) have produced external quantum efficiencies (EQEs) of more than 25% with narrowband emission1,2, but these LEDs have limited operating lifetimes. We posit that poor long-range ordering in perovskite QD films-variations in dot size, surface ligand density and dot-to-dot stacking-inhibits carrier injection, resulting in inferior operating stability because of the large bias required to produce emission in these LEDs. Here we report a chemical treatment to improve the long-range order of perovskite QD films: the diffraction intensity from the repeating QD units increases three-fold compared with that of controls. We achieve this using a synergistic dual-ligand approach: an iodide-rich agent (aniline hydroiodide) for anion exchange and a chemically reactive agent (bromotrimethylsilane) that produces a strong acid that in situ dissolves smaller QDs to regulate size and more effectively removes less conductive ligands to enable compact, uniform and defect-free films. These films exhibit high conductivity (4 × 10-4 S m-1), which is 2.5-fold higher than that of the control, and represents the highest conductivity recorded so far among perovskite QDs. The high conductivity ensures efficient charge transportation, enabling red perovskite QD-LEDs that generate a luminance of 1,000 cd m-2 at a record-low voltage of 2.8 V. The EQE at this luminance is more than 20%. Furthermore, the stability of the operating device is 100 times better than previous red perovskite LEDs at EQEs of more than 20%.

The metabolic ER stress sensor IRE1α suppresses alternative activation of macrophages and impairs energy expenditure in obesity.

Obesity is associated with metabolic inflammation and endoplasmic reticulum (ER) stress, both of which promote metabolic disease progression. Adipose tissue macrophages (ATMs) are key players orchestrating metabolic inflammation, and ER stress enhances macrophage activation. However, whether ER stress pathways underlie ATM regulation of energy homeostasis remains unclear. Here, we identified inositol-requiring enzyme 1α (IRE1α) as a critical switch governing M1-M2 macrophage polarization and energy balance. Myeloid-specific IRE1α abrogation in Ern1f/f; Lyz2-Cre mice largely reversed high-fat diet (HFD)-induced M1-M2 imbalance in white adipose tissue (WAT) and blocked HFD-induced obesity, insulin resistance, hyperlipidemia and hepatic steatosis. Brown adipose tissue (BAT) activity, WAT browning and energy expenditure were significantly higher in Ern1f/f; Lyz2-Cre mice. Furthermore, IRE1α ablation augmented M2 polarization of macrophages in a cell-autonomous manner. Thus, IRE1α senses protein unfolding and metabolic and immunological states, and consequently guides ATM polarization. The macrophage IRE1α pathway drives obesity and metabolic syndrome through impairing BAT activity and WAT browning.

Podocyte-specific Nup160 knockout mice develop nephrotic syndrome and glomerulosclerosis.

More than 60 monogenic genes mutated in steroid-resistant nephrotic syndrome (SRNS) have been identified. Our previous study found that mutations in nucleoporin 160 kD (NUP160) are implicated in SRNS. The NUP160 gene encodes a component of the nuclear pore complex. Recently, two siblings with homozygous NUP160 mutations presented with SRNS and a nervous system disorder. However, replication of nephrotic syndrome (NS)-associated phenotypes in a mammalian model following loss of Nup160 is needed to prove that NUP160 mutations cause SRNS. Here, we generated a podocyte-specific Nup160 knockout (Nup160podKO) mouse model using CRISPR/Cas9 and Cre/loxP technologies. We investigated NS-associated phenotypes in these Nup160podKO mice. We verified efficient abrogation of Nup160 in Nup160podKO mice at both the DNA and protein levels. We showed that Nup160podKO mice develop typical signs of NS. Nup160podKO mice exhibited progression of proteinuria to average albumin/creatinine ratio (ACR) levels of 15.06 ± 2.71 mg/mg at 26 weeks, and had lower serum albumin levels of 13.13 ± 1.34 g/l at 30 weeks. Littermate control mice had urinary ACR mean values of 0.03 mg/mg and serum albumin values of 22.89 ± 0.34 g/l at the corresponding ages. Further, Nup160podKO mice exhibited glomerulosclerosis compared with littermate control mice. Podocyte-specific Nup160 knockout in mice led to NS and glomerulosclerosis. Thus, our findings strongly support that mutations in NUP160 cause SRNS. The newly generated Nup160podKO mice are a reliable mammalian model for future study of the pathogenesis of NUP160-associated SRNS.

Metalens for Accelerated Optoelectronic Edge Detection under Ambient Illumination.

Analog systems may allow image processing, such as edge detection, with low computational power. However, most demonstrated analog systems, based on either conventional 4-f imaging systems or nanophotonic structures, rely on coherent laser sources for illumination, which significantly restricts their use in routine imaging tasks with ambient, incoherent illumination. Here, we demonstrated a metalens-assisted imaging system that can allow optoelectronic edge detection under ambient illumination conditions. The metalens was designed to generate polarization-dependent optical transfer functions (OTFs), resulting in a synthetic OTF with an isotropic high-pass frequency response after digital subtraction. We integrated the polarization-multiplexed metalens with a polarization camera and experimentally demonstrated single-shot edge detection of indoor and outdoor scenes, including a flying airplane, under ambient sunlight illumination. The proposed system showcased the potential of using polarization multiplexing for the construction of complex optical convolution kernels toward accelerated machine vision tasks such as object detection and classification under ambient illumination.

Polarity-Mediated Antisolvent Control Enables Efficient Lanthanide-Based near-Infrared Perovskite LEDs.

Alloying lanthanide ions (Yb3+) into perovskite quantum dots (Yb3+:CsPb(Cl1-xBrx)3) is an effective method to achieve efficient near-infrared (NIR) luminescence (>950 nm). Increasing the Yb3+ alloying ratio in the perovskite matrix enhances the luminescence intensity of Yb3+ emission at 990 nm. However, high Yb3+ alloying (>15%) results in vacancy-induced inferior material stability. In this work, we developed a polarity-mediated antisolvent manipulation strategy to resolve the incompatibility between a high Yb3+ alloying ratio and inferior stability of Yb3+:CsPb(Cl1-xBrx)3. Precise control of solution polarity enables increased uniformity of the perovskite matrix with fewer trap densities. Employing this strategy, we obtain Yb3+:CsPb(Cl1-xBrx)3 with the highest Yb3+ alloying ratio of 30.2% and a 2-fold higher electroluminescence intensity at 990 nm. We lever the engineered Yb3+:CsPb(Cl1-xBrx)3 to fabricate NIR-LEDs, achieving a peak external quantum efficiency (EQE) of 8.5% at 990 nm: this represents the highest among perovskite NIR-LEDs with an emission wavelength above 950 nm.

Enhanced Storage Capacity via Anion Substitution for Advanced Delayed X-ray Detection.

X-ray radiation information storage, characterized by its ability to detect radiation with delayed readings, shows great promise in enabling reliable and readily accessible X-ray imaging and dosimetry in situations where conventional detectors may not be feasible. However, the lack of specific strategies to enhance the memory capability dramatically hampers its further development. Here, we present an effective anion substitution strategy to enhance the storage capability of NaLuF4:Tb3+ nanocrystals attributed to the increased concentration of trapping centers under X-ray irradiation. The stored radiation information can be read out as optical brightness via thermal, 980 nm laser, or mechanical stimulation, avoiding real-time measurement under ionizing radiation. Moreover, the radiation information can be maintained for more than 13 days, and the imaging resolution reaches 14.3 lp mm-1. These results demonstrate that anion substitution methods can effectively achieve high storage capability and broaden the application scope of X-ray information storage.

Controllable Fluorocarbon Chain Elongation: TMSCF2Br-Enabled Trifluorovinylation and Pentafluorocyclopropylation of Aldehydes.

Controllable fluorocarbon chain elongation (CFCE) is a promising yet underdeveloped strategy for the well-defined synthesis of structurally novel polyfluorinated compounds. Herein, the direct and efficient trifluorovinylation and pentafluorocyclopropylation of aldehydes are described by using TMSCF2Br (TMS = trimethylsilyl) as the sole fluorocarbon source, accomplishing the goals of CFCE from C1 to C2 and from C1 to C3, respectively. The key to the success of these CFCE processes lies in the unique and diversified chemical reactivity of TMSCF2Br, which can serve as two different precursors, namely, a TMSCF2 radical precursor and a difluorocarbene precursor. Various functional groups are amenable to this new synthetic protocol, providing streamlined access to a broad range of alcohols containing trifluorovinyl or pentafluorocyclopropyl moieties from abundantly available aldehydes. The potential utility of these methods is further demonstrated by the gram-scale synthesis, derivatization, and measurement of log P values of the products.

USP43 impairs cisplatin sensitivity in epithelial ovarian cancer through HDAC2-dependent regulation of Wnt/ß-catenin signaling pathway.

Epithelial ovarian cancer (EOC) is the leading cause of cancer death all over the world. USP43 functions as a tumor promoter in various malignant cancers. Nevertheless, the biological roles and mechanisms of USP43 in EOC remain unknown. In this study, USP43 was highly expressed in EOC tissues and cells, and high expression of USP43 were associated with a poor prognosis of EOC. USP43 overexpression promoted EOC cell proliferation, enhanced the ability of migration and invasion, decreased cisplatin sensitivity and inhibited apoptosis. Knockdown of USP43 in vitro effectively retarded above malignant progression of EOC. In vivo xenograft tumors, silencing USP43 slowed tumor growth and enhanced cisplatin sensitivity. Mechanistically, USP43 inhibited HDAC2 degradation and enhanced HDAC2 protein stability through its deubiquitylation function. USP43 diminished the sensitivity of EOC cells to cisplatin through activation of the Wnt/ß-catenin signaling pathway mediated by HDAC2. Taken together, the data in this study revealed the functions of USP43 in proliferation, migration, invasion, chemoresistance of EOC cells, and the mechanism of HDAC2-mediated Wnt/ß-catenin signaling pathway. Thus, USP43 might serve as a potential target for the control of ovarian cancer progression.

Field Detection of Uranyl in Coastal Water of China Using a Portable Device via DNA Photocleavage.

The urgent need for field detection of uranium in seawater is 2-fold: to provide prompt guidance for uranium extraction and to prevent human exposure to nuclear radiation. However, current methods for this purpose are largely hindered by bulky instrumentation, high costs of developed materials, and severe matrix interferences, which limit their further application in the field. Herein, we demonstrated a portable and label-free strategy for the field detection of uranyl in seawater based on the efficient photocleavage of DNA. Further experiments confirmed the generation of ultraviolet (UV) light-induced reactive oxygen species (ROS), such as O2•- and •OH, which fragmented oligomeric DNA in the presence of uranyl and UV light. Detailed studies showed that DNA significantly enhances uranyl absorption in the UV-visible region, leading to the generation of more ROS. A fluorescence system for the selective detection of uranyl in seawater was established by immobilizing two complementary oligonucleotides with the fluorescent dye SYBR Green I. The strategy of UV-induced photocleavage offers high selectivity, excellent interference immunity, and high sensitivity for uranyl, with a detection limit of 6.8 nM. Additionally, the fluorescence can be visually detected using a 3D-printed miniaturized device integrated with a smartphone. This method has been successfully applied to the on-site detection of uranyl in seawater in 18 Chinese coastal cities and along the coast of Hainan Island within 3 min for a single sample. The sample testing and field analysis results indicate that this strategy has promising potential for real-time monitoring of trace uranyl in China's coastal waters. It is expected to be utilized for the rapid assessment of nuclear contamination and nuclear engineering construction.

Altered intersubject functional variability of brain white-matter in major depressive disorder and its association with gene expression profiles.

Major depressive disorder (MDD) is a clinically heterogeneous disorder. Its mechanism is still unknown. Although the altered intersubject variability in functional connectivity (IVFC) within gray-matter has been reported in MDD, the alterations to IVFC within white-matter (WM-IVFC) remain unknown. Based on the resting-state functional MRI data of discovery (145 MDD patients and 119 healthy controls [HCs]) and validation cohorts (54 MDD patients, and 78 HCs), we compared the WM-IVFC between the two groups. We further assessed the meta-analytic cognitive functions related to the alterations. The discriminant WM-IVFC values were used to classify MDD patients and predict clinical symptoms in patients. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging association analyses were further conducted to investigate gene expression profiles associated with WM-IVFC alterations in MDD, followed by a set of gene functional characteristic analyses. We found extensive WM-IVFC alterations in MDD compared to HCs, which were associated with multiple behavioral domains, including sensorimotor processes and higher-order functions. The discriminant WM-IVFC could not only effectively distinguish MDD patients from HCs with an area under curve ranging from 0.889 to 0.901 across three classifiers, but significantly predict depression severity (r = 0.575, p = 0.002) and suicide risk (r = 0.384, p = 0.040) in patients. Furthermore, the variability-related genes were enriched for synapse, neuronal system, and ion channel, and predominantly expressed in excitatory and inhibitory neurons. Our results obtained good reproducibility in the validation cohort. These findings revealed intersubject functional variability changes of brain WM in MDD and its linkage with gene expression profiles, providing potential implications for understanding the high clinical heterogeneity of MDD.

Stable establishment of organ polarity occurs several plastochrons before primordium outgrowth in Arabidopsis.

In many species, leaves are initiated at the flanks of shoot meristems. Subsequent growth usually occurs mainly in the plane of the leaf blade, which leads to the formation of a bifacial leaf with dorsoventral identities. In a classical set of surgical experiments in potato meristems, Sussex provided evidence that dorsoventrality depends on a signal emanating from the meristem center. Although these results could be reproduced in tomato, this concept has been debated. We revisited these experiments in Arabidopsis, in which a range of markers are available to target the precise site of ablation. Using specific markers for organ founder cells and dorsoventral identity, we were unable to perturb the polarity of leaves and sepals long before organ outgrowth. Although results in Solanaceae suggested that dorsoventral patterning was unstable during early development, we found that, in Arabidopsis, the local information contained within and around the primordium is able to withstand major invasive perturbations, long before polarity is fully established.

Acidified Nitrogen Self-Doped Porous Carbon with Superprotonic Conduction for Applications in Solid-State Proton Battery.

Solid proton electrolytes play a crucial role in various electrochemical energy storage and conversion devices. However, the development of fast proton conducting solid proton electrolytes at ambient conditions remains a significant challenge. In this study, a novel acidified nitrogen self-doped porous carbon material is presented that demonstrates exceptional superprotonic conduction for applications in solid-state proton battery. The material, designated as MSA@ZIF-8-C, is synthesized through the acidification of nitrogen-doped porous carbon, specifically by integrating methanesulfonic acid (MSA) into zeolitic imidazolate framework-derived nitrogen self-doped porous carbons (ZIF-8-C). This study reveals that MSA@ZIF-8-C achieves a record-high proton conductivity beyond 10-2  S cm-1 at ambient condition, along with good long-term stability, positioning it as a cutting-edge alternative solid proton electrolyte to the default aqueous H2 SO4 electrolyte in proton batteries.

Temperature-Dependent Color-Tunable Afterglow in Zirconium-Doped CsCdCl3 Perovskite for Advanced Anti-Counterfeiting and Thermal Distribution Detection.

Persistent luminescence (PersL) materials exhibit thermal-favored optical behavior, enabling their unique applications in security night vision signage, in vivo bioimaging, and optical anti-counterfeiting. Therefore, developing efficient and color-tunable PersL materials is significantly crucial in promoting advanced practical use. In this study, hexagonal Zr4+ -doped CsCdCl3 perovskite is synthesized via a hydrothermal reaction with a tunable photoluminescent (PL) behavior through heterovalent substitution. Moreover, the incorporation of Zr4+ ions result in an extra blue emission band, originating from the enhanced excitonic recombination in D3d octahedrons. Furthermore, the afterglow performances of the samples are dramatically improved, along with the noticeable temperature-dependent PersL as well as the thermo-luminescence with tunable color output. Detailed analysis reveals that the unique temperature-dependent PersL and thermo-luminescence color change are attributed to the presence of multiple luminous centers and abundant traps. Overall, this work facilitates the development of optical intelligence platforms and novel thermal distribution probes with the as-developed halides perovskite for its superior explored PersL characteristic.

SPLDExtraTrees: robust machine learning approach for predicting kinase inhibitor resistance.

Drug resistance is a major threat to the global health and a significant concern throughout the clinical treatment of diseases and drug development. The mutation in proteins that is related to drug binding is a common cause for adaptive drug resistance. Therefore, quantitative estimations of how mutations would affect the interaction between a drug and the target protein would be of vital significance for the drug development and the clinical practice. Computational methods that rely on molecular dynamics simulations, Rosetta protocols, as well as machine learning methods have been proven to be capable of predicting ligand affinity changes upon protein mutation. However, the severely limited sample size and heavy noise induced overfitting and generalization issues have impeded wide adoption of machine learning for studying drug resistance. In this paper, we propose a robust machine learning method, termed SPLDExtraTrees, which can accurately predict ligand binding affinity changes upon protein mutation and identify resistance-causing mutations. Especially, the proposed method ranks training data following a specific scheme that starts with easy-to-learn samples and gradually incorporates harder and diverse samples into the training, and then iterates between sample weight recalculations and model updates. In addition, we calculate additional physics-based structural features to provide the machine learning model with the valuable domain knowledge on proteins for these data-limited predictive tasks. The experiments substantiate the capability of the proposed method for predicting kinase inhibitor resistance under three scenarios and achieve predictive accuracy comparable with that of molecular dynamics and Rosetta methods with much less computational costs.

itol.toolkit accelerates working with iTOL (Interactive Tree of Life) by an automated generation of annotation files.

SUMMARY: iTOL is a powerful and comprehensive phylogenetic tree visualization engine. However, adjusting to new templates can be time-consuming, especially when many templates are available. We developed an R package namely itol.toolkit to help users generate all 23 types of annotation files in iTOL. This R package also provides an all-in-one data structure to store data and themes, accelerating the step from metadata to annotation files of iTOL visualizations through automatic workflows. AVAILABILITY AND IMPLEMENTATION: The manual and source code are available at https://github.com/TongZhou2017/itol.toolkit.

Delta-sigma modulation supporting the 4194304QAM dual polarization signal at the W-band transmission over a 4.6†km wireless distance.

In this Letter, we propose a dual-polarized coherent millimeter-wave system based on differential delta-sigma modulation (D-DSM) intended for long-distance wireless transmission in the W-band. The proposed system can transmit polarization-division-multiplexed (PDM) D-DSM signals with modulation orders up to 4194304QAM over a wireless channel for 4.6 km at a signal baud rate of 20 G. After 4.6 km of wireless transmission, we successfully achieve a bit error rate (BER) lower than the hard-decision forward error correction (HD-FEC) of 3.8 × 10-3 for 34.51 Gbit/s PDM-524288QAM and a BER lower than the soft-decision forward error correction (SD-FEC) of 4.2 × 10-2 for 32.23 Gbit/s PDM-4194304QAM.

High-order QAM NANF transmission utilizing MIMO equalizer integrated with low-complexity decision-directed carrier phase estimation.

We experimentally realized a high-speed nested anti-resonant nodeless fiber (NANF) transmission with the assistance of the polarization division multiplexing (PDM) and probabilistic shaping (PS) technology. In this system, a low-complexity multiple-input multiple-output (MIMO) real-valued equalizer (RVE) is integrated with decision-directed carrier phase estimation (DDCPE), which is robust against the IQ cross talk and a tiny phase disturbance between PS symbols. By using the proposed MIMO-RVEDDCPE, the 60-Gbaud PDM-PS-256QAM signal has been delivered through 2-km NANF satisfying the soft-decision forward error correction (SD-FEC) threshold.

Heterogeneous changes in gut and tumor microbiota in patients with pancreatic cancer: insights from clinical evidence.

BACKGROUND: Pancreatic cancer is the foremost contributor to cancer-related deaths globally, and its prevalence continues to rise annually. Nevertheless, the underlying mechanisms behind its development remain unclear and necessitate comprehensive investigation. METHODS: In this study, a total of 29 fresh stool samples were collected from patients diagnosed with pancreatic cancer. The gut microbial data of healthy controls were obtained from the SRA database (SRA data number: SRP150089). Additionally, 28 serum samples and diseased tissues were collected from 14 patients with confirmed pancreatic cancer and 14 patients with chronic pancreatitis. Informed consent was obtained from both groups of patients. Microbial sequencing was performed using 16s rRNA. RESULTS: The results showed that compared with healthy controls, the species abundance index of intestinal flora in patients with pancreatic cancer was increased (P < 0.05), and the number of beneficial bacteria at the genus level was reduced (P < 0.05). Compared with patients with chronic pancreatitis, the expression levels of CA242 and CA199 in the serum of patients with pancreatic cancer were increased (P < 0.05). The bacterial richness index of tumor microorganisms in patients with pancreatic cancer increased, while the diversity index decreased(P < 0.05). Furthermore, there was a change in the species composition at the genus level. Additionally, the expression level of CA242 was found to be significantly positively correlated with the relative abundance of Acinetobacter(P < 0.05). CONCLUSION: Over all, the expression levels of serum tumor markers CA242 and CA19-9 in patients with pancreatic cancer are increased, while the beneficial bacteria in the intestine and tumor microenvironment are reduced and pathogenic bacteria are increased. Acinetobacter is a specific bacterial genus highly expressed in pancreatic cancer tissue.

Multitask Deep Learning-Based Whole-Process System for Automatic Diagnosis of Breast Lesions and Axillary Lymph Node Metastasis Discrimination from Dynamic Contrast-Enhanced-MRI: A Multicenter Study.

BACKGROUND: Accurate diagnosis of breast lesions and discrimination of axillary lymph node (ALN) metastases largely depend on radiologist experience. PURPOSE: To develop a deep learning-based whole-process system (DLWPS) for segmentation and diagnosis of breast lesions and discrimination of ALN metastasis. STUDY TYPE: Retrospective. POPULATION: 1760 breast patients, who were divided into training and validation sets (1110 patients), internal (476 patients), and external (174 patients) test sets. FIELD STRENGTH/SEQUENCE: 3.0T/dynamic contrast-enhanced (DCE)-MRI sequence. ASSESSMENT: DLWPS was developed using segmentation and classification models. The DLWPS-based segmentation model was developed by the U-Net framework, which combined the attention module and the edge feature extraction module. The average score of the output scores of three networks was used as the result of the DLWPS-based classification model. Moreover, the radiologists' diagnosis without and with the DLWPS-assistance was explored. To reveal the underlying biological basis of DLWPS, genetic analysis was performed based on RNA-sequencing data. STATISTICAL TESTS: Dice similarity coefficient (DI), area under receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, and kappa value. RESULTS: The segmentation model reached a DI of 0.828 and 0.813 in the internal and external test sets, respectively. Within the breast lesions diagnosis, the DLWPS achieved AUCs of 0.973 in internal test set and 0.936 in external test set. For ALN metastasis discrimination, the DLWPS achieved AUCs of 0.927 in internal test set and 0.917 in external test set. The agreement of radiologists improved with the DLWPS-assistance from 0.547 to 0.794, and from 0.848 to 0.892 in breast lesions diagnosis and ALN metastasis discrimination, respectively. Additionally, 10 breast cancers with ALN metastasis were associated with pathways of aerobic electron transport chain and cytoplasmic translation. DATA CONCLUSION: The performance of DLWPS indicates that it can promote radiologists in the judgment of breast lesions and ALN metastasis and nonmetastasis. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 3.