Glucocorticoid therapy for sepsis in the AI era: a survey on current and future approaches.

Sepsis, a life-threatening medical condition, manifests as new or worsening organ failures due to a dysregulated host response to infection. Many patients with sepsis have manifested a hyperinflammatory phenotype leading to the identification of inflammatory modulation by corticosteroids as a key treatment modality. However, the optimal use of corticosteroids in sepsis treatment remains a contentious subject, necessitating a deeper understanding of their physiological and pharmacological effects. Our study conducts a comprehensive review of randomized controlled trials (RCTs) focusing on traditional corticosteroid treatment in sepsis, alongside an analysis of evolving clinical guidelines. Additionally, we explore the emerging role of artificial intelligence (AI) in medicine, particularly in diagnosing, prognosticating, and treating sepsis. AI's advanced data processing capabilities reveal new avenues for enhancing corticosteroid therapeutic strategies in sepsis. The integration of AI in sepsis treatment has the potential to address existing gaps in knowledge, especially in the application of corticosteroids. Our findings suggest that combining corticosteroid therapy with AI-driven insights could lead to more personalized and effective sepsis treatments. This approach holds promise for improving clinical outcomes and presents a significant advancement in the management of this complex and often fatal condition.

Oxygen vacancy enhanced photocatalytic activity of Cu2O/TiO2 heterojunction.

In this study, a method was developed to create oxygen vacancies in Cu2O/TiO2 heterojunctions. By varying the amounts of ethylenediaminetetraacetic acid (EDTA), sodium citrate, and copper acetate, Cu2O/TiO2 with different Cu ratios were synthesized. Tests on CO2 photocatalytic reduction revealed that Cu2O/TiO2's performance is influenced by Cu content. The ideal Cu mass fraction in Cu2O/TiO2, determined by inductively coupled plasma (ICP), is between 0.075% and 0.55%, with the highest CO yield being 10.22 µmol g-1 h-1, significantly surpassing pure TiO2. High-resolution transmission electron microscopy and electron paramagnetic resonance studies showed optimal oxygen vacancy in the most effective heterojunction. Density functional theory (DFT) calculations indicated a 0.088 eV lower energy barrier for ∗CO2 to ∗COOH conversion in Cu2O/TiO2 with oxygen vacancy compared to TiO2, suggesting that oxygen vacancies enhance photocatalytic activity.

Log-Euclidean metric based covariance propagation on SPD manifold for continuous-discrete extended Kalman filtering.

For nonlinear systems with continuous dynamic and discrete measurements, a Log-Euclidean metric (LEM) based novel scheme is proposed to refine the covariance integration steps of continuous-discrete Extended Kalman filter (CDEKF). In CDEKF, the covariance differential equation is usually integrated with regular Euclidean matrix operations, which actually ignores the Riemannian structure of underlying space and poses a limit on the further improvement of estimation accuracy. To overcome this drawback, this work proposes to define the covariance variable on the manifold of symmetric positive definite (SPD) matrices and propagate it using the Log-Euclidean metric. To embed the LEM based novel propagation scheme, the manifold integration of the covariance for LEMCDEKF is proposed together with the details of efficient realization, which can integrate the covariance on SPD manifold and avoid the drawback of Euclidean scheme. Numerical simulations certify the new method's superior accuracy than conventional methods.

Thermally Evaporated Metal Halide Perovskites and Their Analogues: Film Fabrication, Applications and Beyond.

Metal halide perovskites emerge as promising semiconductors for optoelectronic devices due to ease of fabrication, attractive photophysical properties, their low cost, highly tunable material properties, and high performance. High-quality thin films of metal halide perovskites are the basis of most of these applications including solar cells, light-emitting diodes, photodetectors, and electronic memristors. A typical fabrication method for perovskite thin films is the solution method, which has several limitations in device reproducibility, adverse environmental impact, and utilization of raw materials. Thermal evaporation holds great promise in addressing these bottlenecks in fabricating high-quality halide perovskite thin films. It also has high compatibility with mass-production platforms that are well-established in industries. This review first introduces the basics of the thermal evaporation method with a particular focus on the critical parameters influencing the thin film deposition. The research progress of the fabrication of metal halide perovskite thin films is further summarized by different thermal evaporation approaches and their applications in solar cells and other optoelectronic devices. Finally, research challenges and future opportunities for both fundamental research and commercialization are discussed.

Boosting the Performances of Semitransparent Organic Photovoltaics via Synergetic Near-Infrared Light Management.

Semitransparent organic photovoltaics (ST-OPVs) offer promising prospects for application in building-integrated photovoltaic systems and greenhouses, but further improvement of their performance faces a delicate trade-off between the two competing indexes of power conversion efficiency (PCE) and average visible transmittance (AVT). Herein, the authors take advantage of coupling plasmonics with the optical design of ST-OPVs to enhance near-infrared absorption and hence simultaneously improve efficiency and visible transparency to the maximum extent. By integrating core-bishell PdCu@Au@SiO2 nanotripods that act as optically isotropic Lambertian sources with near-infrared-customized localized surface plasmon resonance in an optimal ternary PM6:BTP-eC9:L8-BO-based ST-OPV, it is shown that their interplay with a multilayer optical coupling layer, consisting of ZnS(130 nm)/Na3AlF6(60 nm)/WO3(100 nm)/LaF3(50 nm) identified from high-throughput optical screening, leads to a record-high PCE of 16.14% (certified as 15.90%) along with an excellent AVT of 33.02%. The strong enhancement of the light utilization efficiency by ≈50% as compared to the counterpart device without optical engineering provides an encouraging and universal pathway for promoting breakthroughs in ST-OPVs from meticulous optical design.

Modular α-tertiary amino ester synthesis through cobalt-catalysed asymmetric aza-Barbier reaction.

Unnatural chiral α-tertiary amino acids containing two different carbon-based substituents at the α-carbon centre are widespread in biologically active molecules. This sterically rigid scaffold is becoming a growing research interest in drug discovery. However, a robust protocol for chiral α-tertiary amino acid synthesis remains scarce due to the challenge of stereoselectively constructing sterically encumbered tetrasubstituted stereogenic carbon centres. Herein we report a cobalt-catalysed enantioselective aza-Barbier reaction of ketimines with various unactivated alkyl halides, including alkyl iodides, alkyl bromides and alkyl chlorides, enabling the formation of chiral α-tertiary amino esters with a high level of enantioselectivity and excellent functional group tolerance. Primary, secondary and tertiary organoelectrophiles are all tolerated in this asymmetric reductive addition protocol, which provides a complementary method for the well-exploited enantioselective nucleophilic addition with moisture- and air-sensitive organometallic reagents. Moreover, the three-component transformation of α-ketoester, amine and alkyl halide represents a formal asymmetric deoxygenative alkylamination of the carbonyl group.

Accelerated Redox Reactions Enable Stable Tin-Lead Mixed Perovskite Solar Cells.

The facile oxidation of Sn2+ to Sn4+ poses an inherent challenge that limits the efficiency and stability of tin-lead mixed (Sn-Pb) perovskite solar cells (PSCs) and all-perovskite tandem devices. In this work, we discover the sustainable redox reactions enabling self-healing Sn-Pb perovskites, where their intractable oxidation degradation can be recovered to their original state under light soaking. Quantitative and operando spectroscopies are used to investigate the redox chemistry, revealing that metallic Pb0 from the photolysis of perovskite reacts with Sn4+ to regenerate Pb2+ and Sn2+ spontaneously. Given the sluggish redox reaction kinetics, V3+ /V2+ ionic pair is designed as an effective redox shuttle to accelerate the recovery of Sn-Pb perovskites from oxidation. The target Sn-Pb PSCs enabled by V3+ /V2+ ionic pair deliver an improved power conversion efficiency (PCE) of 21.22 % and excellent device lifespan, retaining nearly 90 % of its initial PCE after maximum power point tracking under light for 1,000 hours.

Bilayer 2D-3D Perovskite Heterostructures for Efficient and Stable Solar Cells.

With a stacking-layered architecture, the bilayer two-dimensional-three-dimensional (2D-3D) perovskite heterostructure (PHS) not only eliminates surface defects but also protects the 3D perovskite matrix from external stimuli. However, these bilayer 2D-3D PHSs suffer from impaired interfacial charge carrier transport due to the relatively insulating 2D perovskite fragments with a random phase distribution. Over the past decade, substantial efforts have been devoted to pioneering molecular and structural designs of the 2D perovskite interlayers for improving their charge carrier mobility, which enables state-of-the-art perovskite solar cells with high power conversion efficiency and exceptional operational stability. Herein, this review offers a comprehensive and up-to-date overview on the recent progress of bilayer 2D-3D PHSs, encompassing advancements on spacer cation engineering, interfacial charge carrier modification, advanced deposition protocols, and characterization techniques. Then, the evolutionary trajectory of bilayer 2D-3D PHSs is outlined by summarizing its mainstream development trends, followed by a perspective discussion about its future research opportunities toward efficient and durable perovskite solar cells.

Network Pharmacology and Experimental Validation of the Anti-Inflammatory Effect of Tingli Dazao Xiefei Decoction in Acute Lung Injury Treatment.

Purpose: Tingli Dazao Xiefei Decoction (TDXD) is a Traditional Chinese Medicine (TCM) formula used to treat acute lung injury (ALI). However, the precise mechanism of TDXD in treating ALI remains unclear. We investigated the therapeutic mechanism of TDXD against ALI using a complementary approach combining network pharmacology, molecular docking, and in vitro and in vivo experiments. Material and Methods: Potential drug targets of TDXD and relevant target genes associated with ALI were retrieved from Chinese medicines and disease genes databases. Bioinformatics technology was employed to screen potential active ingredients and core targets. Validation experiments were conducted using a lipopolysaccharide (LPS)-induced ALI mouse (C57BL/6J) model, LPS-induced inflammatory RAW264.7 cells, and molecular docking between active compounds of TDXD and potential targets. Results: Network pharmacology suggested that the mechanism of TDXD against ALI involved phosphoinositide 3-kinase (PI3K) / protein kinase B (AKT) / phosphatase and tensin homolog (PTEN) and Janus kinase 2 (JAK2) / signal transducer and activator of transcription 3 (STAT3) pathways. Quercetin, ß-sitosterol, kaempferol, isorhamnetin, and L-stepholidine were identified as the main active compounds of TDXD that exerted anti-ALI effects. Molecular docking indicated that these compounds exhibited good binding capabilities (≤ -5kcal/mol) to key targets in PI3K/AKT/PTEN and JAK2/STAT3 signaling pathways. In the animal model, TDXD alleviated injuries and inflammatory responses in lung tissues, accompanied by inhibition of expression of tumor necrosis factor-α (TNF-α), Interleukin-6 (IL-6), STAT3, and Suppressor of Cytokine Signaling 3 (SOCS3) mRNA, and key proteins in PI3K/AKT/PTEN and JAK2/STAT3 pathways (all P values < 0.05). Cell based experiments showed that TDXD dose-dependently inhibited the expression of essential proteins in PI3K/AKT/PTEN and JAK2/STAT3 pathways (P < 0.05). Conclusion: This study revealed that the mechanism of TDXD in ALI treatment might involve simultaneous regulation of PI3K/AKT/PTEN and JAK2/STAT3 pathways.

MRI advances in the imaging diagnosis of tuberculous meningitis: opportunities and innovations.

Tuberculous meningitis (TBM) is not only one of the most fatal forms of tuberculosis, but also a major public health concern worldwide, presenting grave clinical challenges due to its nonspecific symptoms and the urgent need for timely intervention. The severity and the rapid progression of TBM underscore the necessity of early and accurate diagnosis to prevent irreversible neurological deficits and reduce mortality rates. Traditional diagnostic methods, reliant primarily on clinical findings and cerebrospinal fluid analysis, often falter in delivering timely and conclusive results. Moreover, such methods struggle to distinguish TBM from other forms of neuroinfections, making it critical to seek advanced diagnostic solutions. Against this backdrop, magnetic resonance imaging (MRI) has emerged as an indispensable modality in diagnostics, owing to its unique advantages. This review provides an overview of the advancements in MRI technology, specifically emphasizing its crucial applications in the early detection and identification of complex pathological changes in TBM. The integration of artificial intelligence (AI) has further enhanced the transformative impact of MRI on TBM diagnostic imaging. When these cutting-edge technologies synergize with deep learning algorithms, they substantially improve diagnostic precision and efficiency. Currently, the field of TBM imaging diagnosis is undergoing a phase of technological amalgamation. The melding of MRI and AI technologies unquestionably signals new opportunities in this specialized area.

The diagnosis of tuberculous meningitis: advancements in new technologies and machine learning algorithms.

Tuberculous meningitis (TBM) poses a diagnostic challenge, particularly impacting vulnerable populations such as infants and those with untreated HIV. Given the diagnostic intricacies of TBM, there's a pressing need for rapid and reliable diagnostic tools. This review scrutinizes the efficacy of up-and-coming technologies like machine learning in transforming TBM diagnostics and management. Advanced diagnostic technologies like targeted gene sequencing, real-time polymerase chain reaction (RT-PCR), miRNA assays, and metagenomic next-generation sequencing (mNGS) offer promising avenues for early TBM detection. The capabilities of these technologies are further augmented when paired with mass spectrometry, metabolomics, and proteomics, enriching the pool of disease-specific biomarkers. Machine learning algorithms, adept at sifting through voluminous datasets like medical imaging, genomic profiles, and patient histories, are increasingly revealing nuanced disease pathways, thereby elevating diagnostic accuracy and guiding treatment strategies. While these burgeoning technologies offer hope for more precise TBM diagnosis, hurdles remain in terms of their clinical implementation. Future endeavors should zero in on the validation of these tools through prospective studies, critically evaluating their limitations, and outlining protocols for seamless incorporation into established healthcare frameworks. Through this review, we aim to present an exhaustive snapshot of emerging diagnostic modalities in TBM, the current standing of machine learning in meningitis diagnostics, and the challenges and future prospects of converging these domains.

Harnessing gradient gelatin nanocomposite hydrogels: a progressive approach to tackling antibacterial biofilms.

Infectious wounds pose significant challenges due to their susceptibility to bacterial infections, hindering tissue repair. This study introduces gradient gelatin nanocomposite hydrogels for wound healing and antibacterial biofilm management. These hydrogels, synthesized via UV light polymerization, incorporate copper-doped polydopamine nanoparticles (PDA-Cu) and GelMA (gelatin methacrylate). The hydrogels have a unique structure with a porous upper layer and a denser lower layer, ensuring superior swelling (over than 600%) and effective contact with bacterial biofilms. In vitro experiments demonstrate their remarkable antibacterial properties, inhibiting S. aureus and E. coli biofilms by over 45% and 53%, respectively. This antibacterial action is attributed to the regulation of reactive oxygen species (ROS) production, an alternative mechanism to bacterial cell wall disruption. Moreover, the hydrogels exhibit high biocompatibility with mammalian cells, making them suitable for medical applications. In vivo evaluation in a rat wound infection model shows that the gradient hydrogel treatment effectively controls bacterial biofilm infections and accelerates wound healing. The treated wounds have smaller infected areas and reduced bacterial colony counts. Histological analysis reveals reduced inflammation and enhanced granulation tissue formation in treated wounds, highlighting the therapeutic potential of these gradient nanocomposite hydrogels. In summary, gradient gelatin nanocomposite hydrogels offer promising multifunctional capabilities for wound healing and biofilm-related infections, paving the way for innovative medical dressings with enhanced antibacterial properties and biocompatibility.

Mechanisms of bacterial inhibition and tolerance around cold atmospheric plasma.

The grim situation of bacterial infection has undoubtedly become a major threat to human health. In the context of frequent use of antibiotics, a new bactericidal method is urgently needed to fight against drug-resistant bacteria caused by non-standard use of antibiotics. Cold atmospheric plasma (CAP) is composed of a variety of bactericidal species, which has excellent bactericidal effect on microbes. However, the mechanism of interaction between CAP and bacteria is not completely clear. In this paper, we summarize the mechanisms of bacterial killing by CAP in a systematic manner, discuss the responses of bacteria to CAP treatment that are considered to be related to tolerance and their underlying mechanisms, review the recent advances in bactericidal applications of CAP finally. This review indicates that CAP inhibition and tolerance of survival bacteria are a set of closely related mechanisms and suggests that there might be other mechanisms of tolerance to survival bacteria that had not been discovered yet. In conclusion, this review shows that CAP has complex and diverse bactericidal mechanisms, and has excellent bactericidal effect on bacteria at appropriate doses. KEY POINTS: • The bactericidal mechanism of CAP is complex and diverse. • There are few resistant bacteria but tolerant bacteria during CAP treatment. • There is excellent germicidal effect when CAP in combination with other disinfectants.

Uniform nucleation and growth of Cs3Cu2I5 nanocrystals with high luminous efficiency and structural stability and their application in white light-emitting diodes.

Copper-based ternary halide composites have attracted great attention due to their superior chemical stability and optical properties. Herein, we developed an ultrafast high-power ultrasonic synthesis strategy to realize the uniform nucleation and growth of highly luminescent and stable Cs3Cu2I5 nanocrystals (NCs). The as-synthesized Cs3Cu2I5 NCs show uniform hexagonal morphology with an average mean size of 24.4 nm and emit blue light with a high photoluminescence quantum yield (PLQY) of ∼85%. Moreover, the Cs3Cu2I5 NCs exhibit a remarkable stability during continuous eight times heating/cooling cycling tests (303-423 K). We also demonstrated an efficient and stable white light-emitting diode (WLED) with a high luminous efficiency (LE) of 41.5 lm W-1 and a Commission Internationale de l'Eclairage (CIE) color coordinate of (0.33,0.33).

Development and Validation of a Prognostic Risk Model Based on Nature Killer Cells for Serous Ovarian Cancer.

Nature killer (NK) cells are increasingly considered important in tumor microenvironment, but their role in predicting the prognosis of ovarian cancer has not been revealed. This study aimed to develop a prognostic risk model for ovarian cancer based on NK cells. Firstly, differentially expressed genes (DEGs) of NK cells were found by single-cell RNA-sequencing dataset analysis. Based on six NK-cell DEGs identified by univariable, Lasso and multivariable Cox regression analyses, a prognostic risk model for serous ovarian cancer was developed in the TCGA cohort. This model was then validated in three external cohorts, and evaluated as an independent prognostic factor by multivariable Cox regression analysis together with clinical characteristics. With the investigation of the underlying mechanism, a relation between a higher risk score of this model and more immune activities in tumor microenvironment was revealed. Furthermore, a detailed inspection of infiltrated immunocytes indicated that not only quantity, but also the functional state of these immunocytes might affect prognostic risk. Additionally, the potential of this model to predict immunotherapeutic response was exhibited by evaluating the functional state of cytotoxic T lymphocytes. To conclude, this study introduced a novel prognostic risk model based on NK-cell DEGs, which might provide assistance for the personalized management of serous ovarian cancer patients.

Correction: Atomically flat semiconductor nanoplatelets for light-emitting applications.

Correction for 'Atomically flat semiconductor nanoplatelets for light-emitting applications' by Bing Bai et al., Chem. Soc. Rev., 2023, 52, 318-360, https://doi.org/10.1039/D2CS00130F.

Photosensitisation of inkjet printed graphene with stable all-inorganic perovskite nanocrystals.

All-inorganic perovskite nanocrystals (NCs) with enhanced environmental stability are of particular interest for optoelectronic applications. Here we report on the formulation of CsPbX3 (X is Br or I) inks for inkjet deposition and utilise these NCs as photosensitive layers in graphene photodetectors, including those based on single layer graphene (SLG) as well as inkjet-printed graphene (iGr) devices. The performance of these photodetectors strongly depends on the device structure, geometry and the fabrication process. We achieve a high photoresponsivity, R > 106 A W-1 in the visible wavelength range and a spectral response controlled by the halide content of the perovskite NC ink. By utilising perovskite NCs, iGr and gold nanoparticle inks, we demonstrate a fully inkjet-printed photodetector with R ≈ 20 A W-1, which is the highest value reported to date for this type of device. The performance of the perovskite/graphene photodetectors is explained by transfer of photo-generated charge carriers from the perovskite NCs into graphene and charge transport through the iGr network. The perovskite ink developed here enabled realisation of stable and sensitive graphene-based photon detectors. Compatibility of inkjet deposition with conventional Si-technologies and with flexible substrates combined with high degree of design freedom provided by inkjet deposition offers opportunities for partially and fully printed optoelectronic devices for applications ranging from electronics to environmental sciences.

Efficient and bright green InP quantum dot light-emitting diodes enabled by a self-assembled dipole interface monolayer.

The interfacial state between the hole transport layer (HTL) and quantum dots (QDs) plays a crucial role in the optoelectronic performance of light-emitting diodes. Herein, we reported an efficient and bright green indium phosphide (InP) QD-based light-emitting diode (LED) by introducing a self-assembled monolayer of 4-bromo-2-fluorothiophenol (SAM-BFTP) molecule to improve interfacial charge transport in LED devices. The molecular dipole layer at the interface of the QD layer and HTL not only reduces the energy barrier of holes injected into QDs through vacuum energy level shift but also inhibits the fluorescence quenching of QDs caused by the HTL. Moreover, copper ions doped into phosphomolybdic acid (Cu:PMA) is selected as the hole injection layer (HIL) into the device system based on the SAM-BFTP molecule, and as a result, a green InP QD LED (QLED) with a maximum external quantum efficiency (EQE) of 8.46% and a luminance of 18 356 cd m-2 was realized. This work can inform and underpin the future development of InP-based QLEDs with concurrent high efficiency and brightness.

Universal Molecular Control Strategy for Scalable Fabrication of Perovskite Light-Emitting Diodes.

Despite the rapid progress in perovskite light-emitting diodes (PeLEDs), the electroluminescence performance of large-area perovskite devices lags far behind that of laboratory-size ones. Here, we report a 3.5 cm × 3.5 cm large-area PeLED with a record-high external quantum efficiency of 12.1% by creating an amphipathic molecular interface modifier of betaine citrate (BC) between the perovskite layer and the underlying hole transport layer (HTL). It is found that the surface wettability for various HTLs can be efficiently improved as a result of the coexistence of methyl and carboxyl groups in the BC molecules that makes favorable groups to selectively contact with the HTL surface and increases the surface free energy, which greatly facilitates the scalable process of solution-processed perovskite films. Moreover, the luminous performance of perovskite emitters is simultaneously enhanced through the coordination between C═O in the carboxyl groups and Pb dangling bonds.

Atomically flat semiconductor nanoplatelets for light-emitting applications.

The last decade has witnessed extensive breakthroughs and significant progress in atomically flat two-dimensional (2D) semiconductor nanoplatelets (NPLs) in terms of synthesis, growth mechanisms, optical and electronic properties and practical applications. Such NPLs have electronic structures similar to those of quantum wells in which excitons are predominantly confined along the vertical direction, while electrons are free to move in the lateral directions, resulting in unique optical properties, such as extremely narrow emission line width, short photoluminescence (PL) lifetime, high gain coefficient, and giant oscillator strength transition (GOST). These unique optical properties make NPLs favorable for high color purity light-emitting applications, in particular in light-emitting diodes (LEDs), backlights for liquid crystal displays (LCDs) and lasers. This review article first introduces the intrinsic characteristics of 2D semiconductor NPLs with atomic flatness. Subsequently, the approaches and mechanisms for the controlled synthesis of atomically flat NPLs are summarized followed by an insight on recent progress in the mediation of core/shell, core/crown and core/crown@shell structures by selective epitaxial growth of passivation layers on different planes of NPLs. Moreover, an overview of the unique optical properties and the associated light-emitting applications is elaborated. Despite great progress in this research field, there are some issues relating to heavy metal elements such as Cd2+ in NPLs, and the ambiguous gain mechanisms of NPLs and others are the main obstacles that prevent NPLs from widespread applications. Therefore, a perspective is included at the end of this review article, in which the current challenges in this stimulating research field are discussed and possible solutions to tackle these challenges are proposed.