Photo- and electro-chemical strategies for the activations of strong chemical bonds.

The employment of light and/or electricity - alternatively to conventional thermal energy - unlocks new reactivity paradigms as tools for chemical substrate activations. This leads to the development of new synthetic reactions and a vast expansion of chemical spaces. This review summarizes recent developments in photo- and/or electrochemical activation strategies for the functionalization of strong bonds - particularly carbon-heteroatom (C-X) bonds - via: (1) direct photoexcitation by high energy UV light; (2) activation via photoredox catalysis under irradiation with relatively lower energy UVA or blue light; (3) electrochemical reduction; (4) combination of photocatalysis and electrochemistry. Based on the types of the targeted C-X bonds, various transformations ranging from hydrodefunctionalization to cross-coupling are covered with detailed discussions of their reaction mechanisms.

Development of Broad-Spectrum Nanobodies for the Therapy and Diagnosis of SARS-CoV-2 and Its Multiple Variants.

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evaded the efficacy of previously developed antibodies and vaccines, thus remaining a significant global public health threat. Therefore, it is imperative to develop additional antibodies that are capable of neutralizing emerging variants. Nanobodies, as the smallest functional single-domain antibodies, exhibit enhanced stability and penetration ability, enabling them to recognize numerous concealed epitopes that are inaccessible to conventional antibodies. Herein, we constructed an immune library based on the immunization of alpaca with the S1 subunit of the SARS-CoV-2 spike protein, from which two nanobodies, Nb1 and Nb2, were selected using phage display technology for further characterization. Both nanobodies, with the binding residues residing within the receptor-binding domain (RBD) region of the spike, exhibited high affinity toward the S1 subunit. Moreover, they displayed cross-neutralizing activity against both wild-type SARS-CoV-2 and 10 ο variants, including BA.1, BA.2, BA.3, BA.5, BA.2.75, BF.7, BQ.1, EG.5.1, XBB.1.5, and JN.1. Molecular modeling and dynamics simulations predicted that both nanobodies interacted with the viral RBD through their complementarity determining region 1 (CDR1) and CDR2. These two nanobodies are novel tools for the development of therapeutic and diagnostic countermeasures targeting SARS-CoV-2 variants and potentially emerging coronaviruses.

Modeling the Formation of Organic Compounds across Full Volatility Ranges and Their Contribution to Nanoparticle Growth in a Polluted Atmosphere.

Nanoparticle growth influences atmospheric particles' climatic effects, and it is largely driven by low-volatility organic vapors. However, the magnitude and mechanism of organics' contribution to nanoparticle growth in polluted environments remain unclear because current observations and models cannot capture organics across full volatility ranges or track their formation chemistry. Here, we develop a mechanistic model that characterizes the full volatility spectrum of organic vapors and their contributions to nanoparticle growth by coupling advanced organic oxidation modeling and kinetic gas-particle partitioning. The model is applied to Nanjing, a typical polluted city, and it effectively captures the volatility distribution of low-volatility organics (with saturation vapor concentrations <0.3 µg/m3), thus accurately reproducing growth rates (GRs), with a 4.91% normalized mean bias. Simulations indicate that as particles grow from 4 to 40 nm, the relative fractions of GRs attributable to organics increase from 59 to 86%, with the remaining contribution from H2SO4 and its clusters. Aromatics contribute much to condensable organic vapors (∼37%), especially low-volatility vapors (∼61%), thus contributing the most to GRs (32-46%) as 4-40 nm particles grow. Alkanes also contribute 19-35% of GRs, while biogenic volatile organic compounds contribute minimally (<13%). Our model helps assess the climatic impacts of particles and predict future changes.

A Global Seawater Density Distribution Model Using a Convolutional Neural Network.

Seawater density is an important physical property in oceanography that affects the accuracy of calculations such as gravity fields and tidal potentials and the calibration of acoustic and optical oceanographic sensors. In related studies, constant density values are frequently used, which can introduce significant errors. Therefore, this study employs a basic convolutional neural network model to construct a comprehensive model showing the seawater density distribution across the globe. The model takes into account depth, latitude, longitude, and month as inputs. Numerous real seawater datasets were used to train the model, and it has been shown that the model has an absolute mean error and root mean square error of less than 1 kg/m3 in 99% of the test set samples. The model effectively demonstrates the influence of input parameters on the distribution of seawater density. In this paper, we present a newly developed global model for distributing seawater density which is both comprehensive and accurate, surpassing previous models. The utilization of the model presented in this paper for estimating seawater density can minimize errors in theoretical ocean models and serve as a foundation for designing and analyzing ocean exploration systems.

Turn-on stimuli-responsive switch: strategies for activating a new fluorescence channel by pressure.

The stimulus-responsive smart switching of aggregation-induced emission (AIE) features has attracted considerable attention in 4D information encryption, optical sensors and biological imaging. Nevertheless, for some AIE-inactive triphenylamine (TPA) derivatives, activating the fluorescence channel of TPA remains a challenge based on their intrinsic molecular configuration. Here, we took a new design strategy for opening a new fluorescence channel and enhancing AIE efficiency for (E)-1-(((4-(diphenylamino)phenyl)imino)methyl)naphthalen-2-ol. The turn-on methodology employed is based on pressure induction. Combining ultrafast and Raman spectra with high-pressure in situ showed that activating the new fluorescence channel stemmed from restraining intramolecular twist rotation. Twisted intramolecular charge transfer (TICT) and intramolecular vibration were restricted, which induced an increase in AIE efficiency. This approach provides a new strategy for the development of stimulus-responsive smart-switch materials.

Enigma of Urban Gaseous Oxygenated Organic Molecules: Precursor Type, Role of NOx, and Degree of Oxygenation.

Oxidation of volatile organic compounds (VOCs) forms oxygenated organic molecules (OOMs), which contribute to secondary pollution. Herein, we present measurement results of OOMs using chemical ionization mass spectrometry with nitrate as the reagent ion in Shanghai. Compared to those in forests and laboratory studies, OOMs detected at this urban site were of relatively lower degree of oxygenation. This was attributed to the high NOx concentrations (∼44 ppb), which overall showed a suppression on the propagation reactions. As another result, a large fraction of nitrogenous OOMs (75%) was observed, and this fraction further increased to 84% under a high NO/VOC ratio. By applying a novel framework on OOM categorization and supported by VOC measurements, 50 and 32% OOMs were attributed to aromatic and aliphatic precursors, respectively. Furthermore, aromatic OOMs are more oxygenated (effective oxygen number, nOeff = 4-6) than aliphatic ones (nOeff = 3-4), which can be partly explained by the difference in initiation mechanisms and points to possible discrimination in termination reactions. This study highlights the roles of NOx in OOM formation in urban areas, as well as the formation of nitrogenous products that might show discrimination between aromatic and aliphatic VOCs.

Molecular Characterization of Oxygenated Organic Molecules and Their Dominating Roles in Particle Growth in Hong Kong.

Oxygenated organic molecules (OOMs) are critical intermediates linking volatile organic compound oxidation and secondary organic aerosol (SOA) formation. Yet, the understanding of OOM components, formation mechanism, and impacts are still limited, especially for urbanized regions with a cocktail of anthropogenic emissions. Herein, ambient measurements of OOMs were conducted at a regional background site in South China in 2018. The molecular characteristics of OOMs revealed dominant nitrogen-containing products, and the influences of different factors on OOM composition and oxidation state were elucidated. Positive matrix factorization analysis resolved the complex OOM species to factors featured with fingerprint species from different oxidation pathways. A new method was developed to identify the key functional groups of OOMs, which successfully classified the majority species into carbonyls (8%), hydroperoxides (7%), nitrates (17%), peroxyl nitrates (10%), dinitrates (13%), aromatic ring-retaining species (6%), and terpenes (7%). The volatility estimation of OOMs was improved based on their identified functional groups and was used to simulate the aerosol growth process contributed by the condensation of those low-volatile OOMs. The results demonstrate the predominant role of OOMs in contributing sub-100 nm particle growth and SOA formation and highlight the importance of dinitrates and anthropogenic products from multistep oxidation.

Dual transmission channels at metal-MoS2/WSe2 hetero-bilayer interfaces.

van der Waals heterostructures (vdWHs) open the possibility of creating novel semiconductor materials at the atomic scale that demonstrate totally new physics and enable unique functionalities, and have therefore attracted great interest in the fields of advanced electronic and optoelectronic devices. However, the interactions between metals and vdWHs semiconductors require further investigation as they directly affect or limit the advancement of high-performance electronic devices. Here we study the contact behavior of MoS2/WSe2 vdWHs in contact with a series of bulk metals using ab initio electronic structure calculations and quantum transport simulations. Our study shows that dual transmission paths for electrons and holes exist at the metal-MoS2/WSe2 hetero-bilayer interfaces. In addition, the metal-induced bandgap state (MIGS) of the original monolayer disappears due to the creation of the heterolayer, which weakens the Fermi level pinning (FLP) effect. We also find that the creation of the heterolayer causes a change in the Schottky barrier height (SBH) of the non-ohmic contact systems, whilst this does not occur so easily in the ohmic contact systems. In addition, our results indicate that when Al, Ag and Au are in contact with a MoS2/WSe2 hetero-bilayer semiconductor, a low contact barrier exists throughout the whole transmission process causing the charge to tunnel to the MoS2 layer, irrespective of whether the MoS2 is in contact with the metals as the nearest layer or as the next-nearest layer. Our work not only offers new insights into electrical contact issues between metals and hetero-bilayer semiconductors, but also provides guidance for the design of high-performance vdWHs semiconductor devices.

Multiple strategies of improving photocatalytic water splitting efficiency in 2D arsenic sesquichalcogenides.

Improving the solar-to-hydrogen efficiency has always been a significant topic in the field of photocatalysis. Based on first-principles calculations, herein, we propose multiple strategies to improve the photocatalytic properties of 2D arsenic sesquichalcogenides for full water splitting. The new configurations As2STe2 and As2SeTe2 monolayers, derived from the As2Te3 monolayers by surface modification, are manifested to be typical infrared-light driven photocatalysts. Notably, under the built-in electric field, As2STe2 and As2SeTe2 monolayers can fulfil overall water splitting and the predicted solar-to-hydrogen efficiencies even reach up to 36.19% and 29.36%, respectively. The Gibbs free energy calculations indicate that the OER can be successfully driven under light irradiation. In addition, the overpotentials can provide most of the energy for HER when illuminated, especially for As2STe2 with the . In addition, both As2S3 and As2Se3 monolayers are capable of satisfying the conditions for photocatalytic water splitting. Furthermore, the band gaps of As2Se3 and As2S3 can dramatically be narrowed by increasing the number of layers and doping, respectively. These findings provide a theoretical basis for As2X3 monolayers to achieve efficient photocatalytic water splitting.

A noncanonical role of NOD-like receptor NLRP14 in PGCLC differentiation and spermatogenesis.

NOD-like receptors (NLRs) are traditionally recognized as major inflammasome components. The role of NLRs in germ cell differentiation and reproduction is not known. Here, we identified the gonad-specific Nlrp14 as a pivotal regulator in primordial germ cell-like cell (PGCLC) differentiation in vitro. Physiologically, knock out of Nlrp14 resulted in reproductive failure in both female and male mice. In adult male mice, Nlrp14 knockout (KO) inhibited differentiation of spermatogonial stem cells (SSCs) and meiosis, resulting in trapped SSCs in early stages, severe oligozoospermia, and sperm abnormality. Mechanistically, NLRP14 promoted spermatogenesis by recruiting a chaperone cofactor, BAG2, to bind with HSPA2 and form the NLRP14-HSPA2-BAG2 complex, which strongly inhibited ChIP-mediated HSPA2 polyubiquitination and promoted its nuclear translocation. Finally, loss of HSPA2 protection and BAG2 recruitment by NLRP14 was confirmed in a human nonsense germline variant associated with male sterility. Together, our data highlight a unique proteasome-mediated, noncanonical function of NLRP14 in PGCLC differentiation and spermatogenesis, providing mechanistic insights of gonad-specific NLRs in mammalian germline development.

Drift Error Compensation Algorithm for Heterodyne Optical Seawater Refractive Index Monitoring of Unstable Signals.

The refractive index measurement of seawater has proven significance in oceanography, while an optical heterodyne interferometer is an important, highly accurate, tool used for seawater refractive index measurement. However, for practical seawater refractive index measurement, the refractive index of seawater needs to be monitored for long periods of time, and the influence of drift error on the measurement results for these cases cannot be ignored. This paper proposes a drift error compensation algorithm based on wavelet decomposition, which can adaptively separate the background from the signal, and then calculate the frequency difference to compensate for the drift error. It is suitable for unstable signals, especially signals with large differences between the beginning and the end, which is common in actual seawater refractive index monitoring. The authors identify that the primary cause of drift error is the frequency instability of the acousto-optic frequency shifter (AOFS), and the actual frequency difference was measured through experimentation. The frequency difference was around 0.1 Hz. Simulation experiments were designed to verify the effectiveness of the algorithm, and the standard deviation of the optical length of the results was on the scale of 10-8 m. Liquid refractive index measurement experiments were carried out in a laboratory, and the measurement error was reduced from 36.942% to 0.592% after algorithm processing. Field experiments were carried out regarding seawater refractive index monitoring, and the algorithm-processing results are able to match the motion of the target vehicle. The experimental data were processed with different algorithms, and, according to the comparison of the results, the proposed algorithm performs better than other existing drift error elimination algorithms.

Dearomatization of (Hetero)arenes through Photodriven Interplay between Polysulfide Anions and Formate.

The facile construction of C(sp3 )-rich carbo- and heterocyclic compounds is a pivotal synthetic strategy to foster contemporary drug discovery programs. The downstream dearomatization of readily accessible two-dimensional (2D) planar arenes represents a direct pathway towards accessing three-dimensional (3D) aliphatic scaffolds. Here, we demonstrate that polysulfide anions are capable of catalyzing a dearomatization process of substituted naphthalenes, indoles, and other related heteroaromatic compounds in the presence of potassium formate and methanol under visible light irradiation. The developed protocol exhibits broad functional group tolerance, operational simplicity, scalability, and cost-effectiveness, representing a practical and sustainable synthetic tool for the arene dearomatization.

Relapsing cellulitis associated with Campylobacter coli bacteremia in a Good's syndrome patient: a case report.

BACKGROUND: Good's syndrome (GS) is characterized by immunodeficiency, and patients diagnosed with GS are susceptible to infection or even bacteremia, which is the most evident complication. Campylobacter coli (C. coli) rarely causes bacteremia or extraintestinal infection. We report herein a case with GS in which right leg cellulitis associated with C. coli bacteremia occurred three times over one and a half years. CASE PRESENTATION: A 41-year-old Chinese male with GS was diagnosed with C. coli infection. He presented with swelling and redness of right lower leg and developed bacteremia due to C. coli repeatedly. Bacteremia was confirmed by bacteriological examination. Adding long-term oral antibiotic treatment with amoxicillin/clavulanate potassium and gentamicin following intravenous meropenem and amikacin was very effective. The blood cultures became negative and the patient has been free from any symptoms encountered for more than one year without relapse of bacteremia. CONCLUSIONS: Patients with GS and their physicians should carefully consider the antibacterial treatment options against C. coli bacteremia. Combined anti-infective therapy involving aminoglycoside is preferred in the treatment of C. coli bacteremia in GS patients.

An updated HACOR score for predicting the failure of noninvasive ventilation: a multicenter prospective observational study.

BACKGROUND: Heart rate, acidosis, consciousness, oxygenation, and respiratory rate (HACOR) have been used to predict noninvasive ventilation (NIV) failure. However, the HACOR score fails to consider baseline data. Here, we aimed to update the HACOR score to take into account baseline data and test its predictive power for NIV failure primarily after 1-2 h of NIV. METHODS: A multicenter prospective observational study was performed in 18 hospitals in China and Turkey. Patients who received NIV because of hypoxemic respiratory failure were enrolled. In Chongqing, China, 1451 patients were enrolled in the training cohort. Outside of Chongqing, another 728 patients were enrolled in the external validation cohort. RESULTS: Before NIV, the presence of pneumonia, cardiogenic pulmonary edema, pulmonary ARDS, immunosuppression, or septic shock and the SOFA score were strongly associated with NIV failure. These six variables as baseline data were added to the original HACOR score. The AUCs for predicting NIV failure were 0.85 (95% CI 0.84-0.87) and 0.78 (0.75-0.81) tested with the updated HACOR score assessed after 1-2 h of NIV in the training and validation cohorts, respectively. A higher AUC was observed when it was tested with the updated HACOR score compared to the original HACOR score in the training cohort (0.85 vs. 0.80, 0.86 vs. 0.81, and 0.85 vs. 0.82 after 1-2, 12, and 24 h of NIV, respectively; all p values < 0.01). Similar results were found in the validation cohort (0.78 vs. 0.71, 0.79 vs. 0.74, and 0.81 vs. 0.76, respectively; all p values < 0.01). When 7, 10.5, and 14 points of the updated HACOR score were used as cutoff values, the probability of NIV failure was 25%, 50%, and 75%, respectively. Among patients with updated HACOR scores of ≤ 7, 7.5-10.5, 11-14, and > 14 after 1-2 h of NIV, the rate of NIV failure was 12.4%, 38.2%, 67.1%, and 83.7%, respectively. CONCLUSIONS: The updated HACOR score has high predictive power for NIV failure in patients with hypoxemic respiratory failure. It can be used to help in decision-making when NIV is used.

Single-cell RNA-sequencing analysis and characterisation of testicular cells in giant panda (Ailuropoda melanoleuca).

CONTEXT: The giant panda (Ailuropoda melanoleuca ) is a rare and endangered species to be preserved in China. The giant panda has a low reproductive capacity, and due to the scarcity of samples, studies on testes from giant panda are very limited, with little knowledge about the process of spermatogenesis in this species. AIMS: To establish the gene expression profiles in cells from the testis of a giant panda. METHODS: The 10×Genomics single-cell RNA-sequencing platform was applied to cells from the testis of an adult giant panda. KEY RESULTS: We identified eight testicular cell types including six somatic and two germ cell types from our single-cell RNA-sequencing datasets. We also identified the differentially expressed genes (DEGs) in each cell type, and performed functional enrichment analysis for the identified testicular cell types. Furthermore, by immunohistochemistry we explored the protein localisation patterns of several marker genes in testes from giant panda. CONCLUSIONS: Our study has for the first time established the gene expression profiles in cells from the testis of a giant panda. IMPLICATIONS: Our data provide a reference catalogue for spermatogenesis and testicular cells in the giant panda, laying the foundation for future breeding and preservation of this endangered species.

Semantic Segmentation of Hyperspectral Remote Sensing Images Based on PSE-UNet Model.

With the development of deep learning, the use of convolutional neural networks (CNN) to improve the land cover classification accuracy of hyperspectral remote sensing images (HSRSI) has become a research hotspot. In HSRSI semantics segmentation, the traditional dataset partition method may cause information leakage, which poses challenges for a fair comparison between models. The performance of the model based on "convolutional-pooling-fully connected" structure is limited by small sample sizes and high dimensions of HSRSI. Moreover, most current studies did not involve how to choose the number of principal components with the application of the principal component analysis (PCA) to reduce dimensionality. To overcome the above challenges, firstly, the non-overlapping sliding window strategy combined with the judgment mechanism is introduced, used to split the hyperspectral dataset. Then, a PSE-UNet model for HSRSI semantic segmentation is designed by combining PCA, the attention mechanism, and UNet, and the factors affecting the performance of PSE-UNet are analyzed. Finally, the cumulative variance contribution rate (CVCR) is introduced as a dimensionality reduction metric of PCA to study the Hughes phenomenon. The experimental results with the Salinas dataset show that the PSE-UNet is superior to other semantic segmentation algorithms and the results can provide a reference for HSRSI semantic segmentation.

Military Surgical Team Performance: The Impact of Familiarity, Team Size, and Nurse Anesthesia Students.

PURPOSE: To examine the key factors impacting surgical team performance in a military medical center. DESIGN: A retrospective, exploratory, cross-sectional design. METHODS: We reviewed 751 orthopedic surgical cases to determine the association of surgical team familiarity, surgical complexity, team size, and the presence of student registered nurse anesthetists (SRNAs) with the surgical performance measures of total operative time, turnover time, and on-time surgical start. FINDINGS: We found increases in surgical team familiarity significantly reduced turnover time by 7.84% (1-0.9216 = 0.0784; P = .0260) after controlling for surgical complexity and the presence of an SRNA on the team. Familiarity did not significantly impact total operative time or the odds of a first case on-time start. With a significant interaction of surgical complexity and team size on total operative time, the surgical complexity marginal effect (at the mean of team size) showed that a one-point increase prolonged total operative time by 6.89% (P < .0001), after controlling for team familiarity and an SRNA. The team size marginal effect (at the mean of surgical complexity) showed that adding one member to the surgical team prolonged total operative time by 6.45% (P < .0001), after controlling for team familiarity and an SRNA. Higher surgical complexity not only increased turnover time by 1.46% (P = .0265) while holding surgical complexity and an SRNA presence constant, but also reduced the likelihood of an on-time surgical start by 0.9359 (P = .0060). Larger teams decreased the odds of an on-time start by 0.7750 (P = .0363). We found that SRNAs potentially offer efficiency benefits, as their presence on a surgical team was associated with a 0.82% (1-0.9185 = 0.0815; P = .0007) decrease in total operative time, and a 21.01% (1-0.7899=0.2101; P = .0002) reduction in expected turnover time, after adjusting for confounding variables. CONCLUSIONS: Surgical efficiency is a modifiable function of surgical teams. Although we suggest additional research, surgical leaders can potentially improve team performance by improving familiarity and forming small and cohesive surgical teams. As OR inefficiencies degrade the financial vitality of healthcare systems, surgical leaders should engage in a multifaceted program to improve efficiency by building familiarity and optimizing team size.

Derivation and external validation of a risk score for predicting HIV-associated tuberculosis to support case finding and preventive therapy scale-up: A cohort study.

BACKGROUND: Among people living with HIV (PLHIV), more flexible and sensitive tuberculosis (TB) screening tools capable of detecting both symptomatic and subclinical active TB are needed to (1) reduce morbidity and mortality from undiagnosed TB; (2) facilitate scale-up of tuberculosis preventive therapy (TPT) while reducing inappropriate prescription of TPT to PLHIV with subclinical active TB; and (3) allow for differentiated HIV-TB care. METHODS AND FINDINGS: We used Botswana XPRES trial data for adult HIV clinic enrollees collected during 2012 to 2015 to develop a parsimonious multivariable prognostic model for active prevalent TB using both logistic regression and random forest machine learning approaches. A clinical score was derived by rescaling final model coefficients. The clinical score was developed using southern Botswana XPRES data and its accuracy validated internally, using northern Botswana data, and externally using 3 diverse cohorts of antiretroviral therapy (ART)-naive and ART-experienced PLHIV enrolled in XPHACTOR, TB Fast Track (TBFT), and Gugulethu studies from South Africa (SA). Predictive accuracy of the clinical score was compared with the World Health Organization (WHO) 4-symptom TB screen. Among 5,418 XPRES enrollees, 2,771 were included in the derivation dataset; 67% were female, median age was 34 years, median CD4 was 240 cells/µL, 189 (7%) had undiagnosed prevalent TB, and characteristics were similar between internal derivation and validation datasets. Among XPHACTOR, TBFT, and Gugulethu cohorts, median CD4 was 400, 73, and 167 cells/µL, and prevalence of TB was 5%, 10%, and 18%, respectively. Factors predictive of TB in the derivation dataset and selected for the clinical score included male sex (1 point), ≥1 WHO TB symptom (7 points), smoking history (1 point), temperature >37.5°C (6 points), body mass index (BMI) <18.5kg/m2 (2 points), and severe anemia (hemoglobin <8g/dL) (3 points). Sensitivity using WHO 4-symptom TB screen was 73%, 80%, 94%, and 94% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, but increased to 88%, 87%, 97%, and 97%, when a clinical score of ≥2 was used. Negative predictive value (NPV) also increased 1%, 0.3%, 1.6%, and 1.7% in XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively, when the clinical score of ≥2 replaced WHO 4-symptom TB screen. Categorizing risk scores into low (<2), moderate (2 to 10), and high-risk categories (>10) yielded TB prevalence of 1%, 1%, 2%, and 6% in the lowest risk group and 33%, 22%, 26%, and 32% in the highest risk group for XPRES, XPHACTOR, TBFT, and Gugulethu cohorts, respectively. At clinical score ≥2, the number needed to screen (NNS) ranged from 5.0 in Gugulethu to 11.0 in XPHACTOR. Limitations include that the risk score has not been validated in resource-rich settings and needs further evaluation and validation in contemporary cohorts in Africa and other resource-constrained settings. CONCLUSIONS: The simple and feasible clinical score allowed for prioritization of sensitivity and NPV, which could facilitate reductions in mortality from undiagnosed TB and safer administration of TPT during proposed global scale-up efforts. Differentiation of risk by clinical score cutoff allows flexibility in designing differentiated HIV-TB care to maximize impact of available resources.

Förster resonance energy transfer outpaces Auger recombination in CdTe/CdS quantum dots-rhodamine101 molecules system upon compression.

Förster resonance energy transfer (FRET) and Auger recombination in quantum dots (QDs)-molecules system are important mechanisms for affecting performance of their optoelectronic and photosynthesis devices. However, exploring an effective strategy to promote FRET and suppress Auger recombination simultaneously remains a daunting challenge. Here, we report that FRET process is promoted and Auger recombination process is suppressed in CdTe/CdS QDs-Rhodamine101 (Rh101) molecules system upon compression. The greatly improved FRET is attributed to the shortened donor-acceptor distance and increased the number of molecules attached to QDs induced by pressure. The reduced Auger recombination is ascribed to the formation of an alloy layer at the core/shell interface. The FRET can occur 70 times faster than Auger recombination under a high pressure of 0.9 GPa. Our findings demonstrate that high pressure is a robust tool to boost FRET and simultaneously suppress Auger recombination, and provides a new route to QDs-molecules applications.

Toward Building a Physical Proxy for Gas-Phase Sulfuric Acid Concentration Based on Its Budget Analysis in Polluted Yangtze River Delta, East China.

Gaseous sulfuric acid (H2SO4) is a crucial precursor for secondary aerosol formation, particularly for new particle formation (NPF) that plays an essential role in the global number budget of aerosol particles and cloud condensation nuclei. Due to technology challenges, global-wide and long-term measurements of gaseous H2SO4 are currently very challenging. Empirical proxies for H2SO4 have been derived mainly based on short-term intensive campaigns. In this work, we performed comprehensive measurements of H2SO4 and related parameters in the polluted Yangtze River Delta in East China during four seasons and developed a physical proxy based on the budget analysis of gaseous H2SO4. Besides the photo-oxidation of SO2, we found that primary emissions can contribute considerably, particularly at night. Dry deposition has the potential to be a non-negligible sink, in addition to condensation onto particle surfaces. Compared with the empirical proxies, the newly developed physical proxy demonstrates extraordinary stability in all the seasons and has the potential to be widely used to improve the understanding of global NPF fundamentally.