Detection of anti-premembrane antibody as a specific marker of four flavivirus serocomplexes and its application to serosurveillance in endemic regions

In the past few decades, several emerging/re-emerging mosquito-borne flaviviruses have resulted in disease outbreaks of public health concern in the tropics and subtropics. Due to cross-reactivities of antibodies recognizing the envelope protein of different flaviviruses, serosurveillance remains a challenge. Previously we reported that anti-premembrane (prM) antibody can discriminate between three flavivirus infections by Western blot analysis. In this study, we aimed to develop a serological assay that can discriminate infection or exposure with flaviviruses from four serocomplexes, including dengue (DENV), Zika (ZIKV), West Nile (WNV) and yellow fever (YFV) viruses, and explore its application for serosurveillance in flavivirus-endemic countries. We employed Western blot analysis including antigens of six flaviviruses (DENV1, 2 and 4, WNV, ZIKV and YFV) from four serocomplexes. We tested serum samples from YF-17D vaccinees, and from DENV, ZIKV and WNV panels that had been confirmed by RT-PCR or by neutralization assays. The overall sensitivity/specificity of anti-prM antibodies for DENV, ZIKV, WNV, and YFV infections/exposure were 91.7%/96.4%, 91.7%/99.2%, 88.9%/98.3%, and 91.3%/92.5%, respectively. When testing 48 samples from Brazil, we identified multiple flavivirus infections/exposure including DENV and ZIKV, DENV and YFV, and DENV, ZIKV and YFV. When testing 50 samples from the Philippines, we detected DENV, ZIKV, and DENV and ZIKV infections with a ZIKV seroprevalence rate of 10%, which was consistent with reports of low-level circulation of ZIKV in Asia. Together, these findings suggest that anti-prM antibody is a flavivirus serocomplex-specific marker and can be employed to delineate four flavivirus infections/exposure in regions where multiple flaviviruses co-circulate.

A High-Entropy Single-Atom Catalyst Toward Oxygen Reduction Reaction in Acidic and Alkaline Conditions

The design of high-entropy single-atom catalysts (HESAC) with 5.2 times higher entropy compared to single-atom catalysts (SAC) is proposed, by using four different metals (FeCoNiRu-HESAC) for oxygen reduction reaction (ORR). Fe active sites with intermetallic distances of 6.1 Å exhibit a low ORR overpotential of 0.44 V, which originates from weakening the adsorption of OH intermediates. Based on density functional theory (DFT) findings, the FeCoNiRu-HESAC with a nitrogen-doped sample were synthesized. The atomic structures are confirmed with X-ray photoelectron spectroscopy (XPS), X-ray absorption (XAS), and scanning transmission electron microscopy (STEM). The predicted high catalytic activity is experimentally verified, finding that FeCoNiRu-HESAC has overpotentials of 0.41 and 0.37 V with Tafel slopes of 101 and 210 mVdec-1 at the current density of 1 mA cm-2 and the kinetic current densities of 8.2 and 5.3 mA cm-2, respectively, in acidic and alkaline electrolytes. These results are comparable with Pt/C. The FeCoNiRu-HESAC is used for Zinc-air battery applications with an open circuit potential of 1.39 V and power density of 0.16 W cm-2. Therefore, a strategy guided by DFT is provided for the rational design of HESAC which can be replaced with high-cost Pt catalysts toward ORR and beyond.

[Clinical application of split liver transplantation: a single center report of 203 cases]

Objective: To investigate the safety and therapeutic effect of split liver transplantation (SLT) in clinical application. Methods: This is a retrospective case-series study. The clinical data of 203 consecutive SLT, 79 living donor liver transplantation (LDLT) and 1 298 whole liver transplantation (WLT) performed at the Third Affiliated Hospital of Sun Yat-sen University from July 2014 to July 2023 were retrospectively analyzed. Two hundred and three SLT liver grafts were obtained from 109 donors. One hundred and twenty-seven grafts were generated by in vitro splitting and 76 grafts were generated by in vivo splitting. There were 90 adult recipients and 113 pediatric recipients. According to time, SLT patients were divided into two groups: the early SLT group (40 cases, from July 2014 to December 2017) and the mature SLT technology group (163 cases, from January 2018 to July 2023). The survival of each group was analyzed and the main factors affecting the survival rate of SLT were analyzed. The Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cumulative survival rates at 1-, 3-, and 5-year were 74.58%, 71.47%, and 71.47% in the early SLT group, and 88.03%, 87.23%, and 87.23% in the mature SLT group, respectively. Survival rates in the mature SLT group were significantly higher than those in the early SLT group (χ2=5.560,P=0.018). The cumulative survival rates at 1-, 3- and 5-year were 93.41%, 93.41%, 89.95% in the LDLT group and 87.38%, 81.98%, 77.04% in the WLT group, respectively. There was no significant difference among the mature SLT group, the LDLT group and the WLT group (χ2=4.016, P=0.134). Abdominal hemorrhage, infection, primary liver graft nonfunction,and portal vein thrombosis were the main causes of early postoperative death. Conclusion: SLT can achieve results comparable to those of WLT and LDLT in mature technology liver transplant centers, but it needs to go through a certain time learning curve.

Predictions of photophysical properties of phosphorescent platinum(II) complexes based on ensemble machine learning approach

Cyclometalated Pt(II) complexes are popular phosphorescent emitters with color-tunable emissions. To render their practical applications as organic light-emitting diodes emitters, it is required to develop Pt(II) complexes with high radiative decay rate constant and photoluminescence (PL) quantum yield. Here, a general protocol is developed for accurate predictions of emission wavelength, radiative decay rate constant, and PL quantum yield based on the combination of first-principles quantum mechanical method, machine learning, and experimental calibration. A new dataset concerning phosphorescent Pt(II) emitters is constructed, with more than 200 samples collected from the literature. Features containing pertinent electronic properties of the complexes are chosen and ensemble learning models combined with stacking-based approaches exhibit the best performance, where the values of squared correlation coefficients are 0.96, 0.81, and 0.67 for the predictions of emission wavelength, PL quantum yield and radiative decay rate constant, respectively. The accuracy of the protocol is further confirmed using 24 recently reported Pt(II) complexes, which demonstrates its reliability for a broad palette of Pt(II) emitters.

Mitochondria-Associated Transcriptome Profiling via Localizable Aggregation-Induced Emission Photosensitizers in Live Cells

In recent decades, there has been increasing interest in studying mitochondria through transcriptomic research. Various exogenous fusion protein-based proximity labeling methods have been reported that focus on the site of one particular protein/peptide and might also influence the corresponding localization or interactome. To enable unbiased and high spatial-resolution profiling of mitochondria-associated transcriptomes in live cells, a flexible RNA proximity labeling approach was developed using aggregation-induced emission (AIE) type photosensitizers (PSs) that possess great mitochondria-targeting capabilities. Their accumulation in an enclosed mitochondrial environment tends to enhance the fluorescence emission and reactive oxygen species generation. By comparing the in vitro optical properties, photosensitization processes, as well as the in cellulo mitochondrial specificity and RNA labeling performance of four AIE PSs, high-throughput sequencing analysis was conducted using TFPy-mediated RNA proximity labeling in live HeLa cells. This approach successfully captured a comprehensive list of transcripts, including mitochondria-encoded RNAs, as well as some nuclear-derived RNAs located at the outer mitochondrial membrane and interacting organelles. This small molecule-based proximity labeling method bypasses complex genetic manipulation and transfection steps, making it readily applicable for diverse research purposes.

Detection of anti-premembrane antibody as a specific marker of four flavivirus serocomplexes and its application to serosurveillance in endemic regions

In the past few decades, several emerging/re-emerging mosquito-borne flaviviruses have resulted in disease outbreaks of public health concern in the tropics and subtropics. Due to cross-reactivities of antibodies recognizing the envelope protein of different flaviviruses, serosurveillance remains a challenge. Previously we reported that anti-premembrane (prM) antibody can discriminate between three flavivirus infections by Western blot analysis. In this study, we aimed to develop a serological assay that can discriminate infection or exposure with flaviviruses from four serocomplexes, including dengue (DENV), Zika (ZIKV), West Nile (WNV) and yellow fever (YFV) viruses, and explore its application for serosurveillance in flavivirus-endemic countries. We employed Western blot analysis including antigens of six flaviviruses (DENV1, 2 and 4, WNV, ZIKV and YFV) from four serocomplexes. We tested serum samples from YF-17D vaccinees, and from DENV, ZIKV and WNV panels that had been confirmed by RT-PCR or by neutralization assays. The overall sensitivity/specificity of anti-prM antibodies for DENV, ZIKV, WNV, and YFV infections/exposure were 91.7%/96.4%, 91.7%/99.2%, 88.9%/98.3%, and 91.3%/92.5%, respectively. When testing 48 samples from Brazil, we identified multiple flavivirus infections/exposure including DENV and ZIKV, DENV and YFV, and DENV, ZIKV and YFV. When testing 50 samples from the Philippines, we detected DENV, ZIKV, and DENV and ZIKV infections with a ZIKV seroprevalence rate of 10%, which was consistent with reports of low-level circulation of ZIKV in Asia. Together, these findings suggest that anti-prM antibody is a flavivirus serocomplex-specific marker and can be employed to delineate four flavivirus infections/exposure in regions where multiple flaviviruses co-circulate.

Construct exchange-correlation functional via machine learning

Density functional theory has been widely used in quantum mechanical simulations, but the search for a universal exchange-correlation (XC) functional has been elusive. Over the last two decades, machine-learning techniques have been introduced to approximate the XC functional or potential, and recent advances in deep learning have renewed interest in this approach. In this article, we review early efforts to use machine learning to approximate the XC functional, with a focus on the challenge of transferring knowledge from small molecules to larger systems. Recently, the transferability problem has been addressed through the use of quasi-local density-based descriptors, which are rooted in the holographic electron density theorem. We also discuss recent developments using deep-learning techniques that target high-level ab initio molecular energy and electron density for training. These efforts can be unified under a general framework, which will also be discussed from this perspective. Additionally, we explore the use of auxiliary machine-learning models for van der Waals interactions.

Mechanical transmission of dengue virus by Aedes aegypti may influence disease transmission dynamics during outbreaks

BACKGROUND

Dengue virus outbreaks are increasing in number and severity worldwide. Viral transmission is assumed to require a minimum time period of viral replication within the mosquito midgut. It is unknown if alternative transmission periods not requiring replication are possible.

METHODS

We used a mouse model of dengue virus transmission to investigate the potential of mechanical transmission of dengue virus. We investigated minimal viral titres necessary for development of symptoms in bitten mice and used resulting parameters to inform a new model of dengue virus transmission within a susceptible population.

FINDINGS

Naïve mice bitten by mosquitoes immediately after they took partial blood meals from dengue infected mice showed symptoms of dengue virus, followed by mortality. Incorporation of mechanical transmission into mathematical models of dengue virus transmission suggest that this supplemental transmission route could result in larger outbreaks which peak sooner.

INTERPRETATION

The potential of dengue transmission routes independent of midgut viral replication has implications for vector control strategies that target mosquito lifespan and suggest the possibility of similar mechanical transmission routes in other disease-carrying mosquitoes.

FUNDING

This study was funded by grants from the National Health Research Institutes, Taiwan (04D2-MMMOST02), the Human Frontier Science Program (RGP0033/2021), the National Institutes of Health (1R01AI143698-01A1, R01AI151004 and DP2AI152071) and the Ministry of Science and Technology, Taiwan (MOST104-2321-B-400-016).

[Regulatory effect of moxibustion on LTB4/MMP-9 in serum of patients with rheumatoid arthritis]

OBJECTIVE

To observe the effects of moxibustion on the contents of leukotriene B4 (LTB4), interleukin-17 (IL-17), tumor necrosis factor-α (TNF-α) and matrix metalloproteinase -9 (MMP-9) in serum, and explore the protection mechanisms of moxibustion in the patients with rheumatoid arthritis (RA).

METHODS

A total of 64 patients with RA were randomly divided into treatment group (n=31) and control group (n=33). The patients in the control group were treated with conventional medication for consecutive 5 weeks. Based on the treatment in the control group, the patients in the treatment group were treated with moxibustion at bilateral Shenshu (BL23), Zusanli (ST36) and Ashi points, 3 times a week, for consecutive 5 weeks. Separately, the visual analogue scale (VAS) score, morning stiffness score, the number of tender joints, the number of swollen joints, the score of the disease activity score of 28 joints (DAS28) were observed; the contents of rheumatoid factor (RF), erythrocyte sedimentation rate (ESR) and C-reative protein (CRP) in serum were determined by biochemical method; and the contents of LTB4, IL-17, TNF-α and MMP-9 in serum were detected by using ELISA before and after treatment in the patients of both groups.

RESULTS

After treatment, VAS score, morning stiffness score, the number of tender joints, the number of swollen joints, DAS28 score, the contents of serum RF in both groups, and contents of serum CRP, ESR, LTB4, IL-17, TNF-α and MMP-9 in the treatment group were significantly reduced when compared with those before treatment (P<0.01, P<0.05). After treatment, VAS score, morning stiffness score, the number of tender joints, the number of swollen joints, DAS28 score, and the levels of LTB4, IL-17 and MMP-9 in serum were obviously lower in the treatment group when compared with the control group (P<0.01, P<0.05). In the treatment group, the changes before and after treatment in the levels of LTB4, IL-17 and TNF-α were positively correlated with that of MMP-9 (P<0.05, r>0).

CONCLUSION

Moxibustion at BL23 and ST36 combined with conventional medication significantly relieves joint pain and reduce disease activity in RA patients, which may be related to the modulation of LTB4, IL-17 and MMP-9 by moxibustion.

Integrated Surface Modulation of Ultrahigh Ni Cathode Materials for Improved Battery Performance

Ni-rich layered cathodes with ultrahigh nickel content (≥90%), for example LiNi_0.9 Co_0.1 O₂ (NC0.9), are promising for next-generation high-energy Li-ion batteries (LIBs), but face stability issues related to structural degradation and side reactions during the electrochemical process. Here, surface modulation is demonstrated by integrating a Li⁺ -conductive nanocoating and gradient lattice doping to stabilize the active cathode efficiently for extended cycles. Briefly, a wet-chemistry process is developed to deposit uniform ZrO(OH)₂ nanoshells around Ni_0.905 Co_0.095 (OH)₂ (NC0.9-OH) hydroxide precursors, followed by high temperature lithiation to create reinforced products featuring Zr doping in the crust lattice decorated with Li₂ ZrO₃ nanoparticles on the surface. It is identified that the Zr⁴⁺ infiltration reconstructed the surface lattice into favorable characters such as Li⁺ deficiency and Ni³⁺ reduction, which are effective to combat side reactions and suppress phase degradation and crack formation. This surface control is able to achieve an optimized balance between surface stabilization and charge transfer, resulting in an extraordinary capacity retention of 96.6% after 100 cycles at 1 C and an excellent rate capability of 148.8 mA h g^-1 at 10 C. This study highlights the critical importance of integrated surface modulation for high stability of cathode materials in next-generation LIBs.

A semilocal machine-learning correction to density functional approximations

Machine learning (ML) has demonstrated its potential usefulness for the development of density functional theory methods. In this work, we construct an ML model to correct the density functional approximations, which adopts semilocal descriptors of electron density and density derivative and is trained by accurate reference data of relative and absolute energies. The resulting ML-corrected functional is tested on a comprehensive dataset including various types of energetic properties. Particularly, the ML-corrected Becke's three parameters and the Lee-Yang-Parr correlation (B3LYP) functional achieves a substantial improvement over the original B3LYP on the prediction of total energies of atoms and molecules and atomization energies, and a marginal improvement on the prediction of ionization potentials, electron affinities, and bond dissociation energies; whereas, it preserves the same level of accuracy for isomerization energies and reaction barrier heights. The ML-corrected functional allows for fully self-consistent-field calculation with similar efficiency to the parent functional. This study highlights the progress of building an ML correction toward achieving a functional that performs uniformly better than B3LYP.

Surface Lattice Modulation through Chemical Delithiation toward a Stable Nickel-Rich Layered Oxide Cathode

Nickel-rich layered oxides (NLOs) are considered as one of the most promising cathode materials for next-generation high-energy lithium-ion batteries (LIBs), yet their practical applications are currently challenged by the unsatisfactory cyclability and reliability owing to their inherent interfacial and structural instability. Herein, we demonstrate an approach to reverse the unstable nature of NLOs through surface solid reaction, by which the reconstructed surface lattice turns stable and robust against both side reactions and chemophysical breakdown, resulting in improved cycling performance. Specifically, conformal La(OH)₃ nanoshells are built with their thicknesses controlled at nanometer accuracy, which act as a Li⁺ capturer and induce controlled reaction with the NLO surface lattices, thereby transforming the particle crust into an epitaxial layer with localized Ni/Li disordering, where lithium deficiency and nickel stabilization are both achieved by transforming oxidative Ni³⁺ into stable Ni²⁺. An optimized balance between surface stabilization and charge transfer is demonstrated by a representative NLO material, namely, LiNi_0.83Co_0.07Mn_0.1O₂, whose surface engineering leads to a highly improved capacity retention and excellent rate capability with a strong capability to inhibit the crack of NLO particles. Our study highlights the importance of surface chemistry in determining chemical and structural behaviors and paves a research avenue in controlling the surface lattice for the stabilization of NLOs toward reliable high-energy LIBs.

Self-Consistent-Charge Density-Functional Tight-Binding Parameters for Modeling an All-Solid-State Lithium Battery

All-solid-state lithium-ion batteries have been a promising solution for next-generation energy storage due to their safety and potentially high energy density. In this work, we developed a density-functional tight-binding (DFTB) parameter set for modeling solid-state lithium batteries, focusing on the band alignment at electrolyte/electrode interfaces. Despite DFTB being widely applied in the simulation of large-scale systems, parametrization is usually done for single materials, and less attention is paid to band alignment among multiple materials. Band offsets at the electrolyte/electrode interfaces are key quantities determining the performance. Here, an automated global optimization method based on DFTB confinement potentials of all elements is developed, while the band offsets between electrodes and electrolytes are introduced as constraints during the optimization. The parameter set is applied to model an all-solid-state Li/Li₂PO₂N/LiCoO₂ battery, and its electronic structure shows a good agreement with that from density-functional theory (DFT) calculations.

High-performance plasmonic polymer modulators through mode hybridization and electro-thermomechanical effects

In this work, an electro-optical polymer modulator with double-layered gold nanostrips, a polymer nanograting, and a metal substrate is proposed and designed. Interestingly, mode hybridization between the Fabry-Pérot (F-P) and anti-bonding modes is formed, and strongly depends on the nanograting size, which can be controllably modulated by an injection current. The simulation and calculation results show that the temperature sensitivity and large structural sensitivity for the polymer modulator could remain constant during the current-tuning process, and a near-zero reflectance and a low linewidth of 13.8 nm in the red region corresponding to a high quality (Q) factor of 51 is achieved. In addition, a large redshift of 60.7 nm and a super-high modulation depth of 424 are obtained at only 8 µA.

A 2-bp deletion in intron 1 of TMEM182 is associated with TMEM182 mRNA expression and chicken body weight

1. Searching for molecular markers related to growth and carcase traits plays a critical role in improvement of the production performance of broilers. Previous studies found that transmembrane protein 182 (TMEM182) inhibits skeletal muscle development, growth, and regeneration, implying that the TMEM182 gene plays an important role during the development process of skeletal muscle.2. A novel 2-bp indel in intron 1 of TMEM182 was detected in a yellow chicken population derived from the cross of White Recessive Rock chickens with Xinghua chickens, and three genotypes II (inserted homozygote), ID (inserted and deleted heterozygote) and DD (deleted homozygote) were observed. Association analyses indicated that the indel was significantly associated with the body weight, muscle fibre area, breast muscle weight and wing weight in the F2 population.3. The expression of TMEM182 in leg muscle of chickens with II genotype was higher than that with DD genotype, with the 2-bp indel located in one of the putative PAX4 binding sites. Further research through luciferase assays revealed that the PAX4 could bind to the putative binding site and increase the TMEM182 transcription, with the 2-bp deletion disrupting the binding of PAX4.4. The present study provides evidence for the association of the novel 2-bp indel in intron 1 of TMEM182 with the growth and carcase traits of chickens. This 2-bp indel could be used as a genetic marker in broiler breeding.

[Clinical efficacy of split liver transplantation in the treatment of children with biliary atresia]

Objective: To compare the clinical efficacy of split liver transplantation (SLT) and living donor liver transplantation(LDLT) in the treatment of children with biliary atresia. Methods: The clinical data of 64 children with biliary atresia who underwent SLT and 44 children who underwent LDLT from June 2017 to May 2022 at Liver Surgery & Liver Transplantation Center,the Third Affiliated Hospital of Sun Yat-sen University were retrospectively analyzed. Among the children who received SLT, there were 40 males and 24 females. The median age at transplantation was 8 months (range:4 to 168 months). Among the patients who received LDLT, there were 24 males and 20 females. The age at transplantation ranged from 4 to 24 months,with a median age of 7 months. Sixty-four children with biliary atresia were divided into two groups according to the SLT operation time: 32 cases in the early SLT group(June 2017 to January 2019) and 32 cases in the technically mature SLT group (February 2019 to May 2022). Rank sum test or t test was used to compare the recovery of liver function between the LDLT group and the SLT group,and between the early SLT group and the technically mature SLT group. The incidence of postoperative complications was compared by χ² test or Fisher exact probability method. Kaplan-Meier method and Log-rank test were used for survival analysis. Results: The cold ischemia time(M (IQR)) (218 (65) minutes), intraoperative blood loss(175 (100) ml) and graft-to-recipient body weight ratio (3.0±0.7) in the LDLT group were lower than those in the SLT group(500 (130) minutes, 200 (250) ml, 3.4±0.8) (Z=-8.064,Z=-2.969, t=-2.048, all P<0.05). The cold ischemia time(457(158)minutes) and total hospital stay ((37.4±22.4)days) in the technically mature SLT group were lower than those in the early SLT group(510(60)minutes, (53.0±39.0)days).The differences were statistically significant (Z=-2.132, t=1.934, both P<0.05).The liver function indexes of LDLT group and SLT group showed unimodal changes within 1 week after operation. The peak values of ALT, AST, prothrombin time, activeated partial thromboplasting time, international normalized ratio, fibrinogen and creatinine all appeared at 1 day after operation, and the peak value of prothrombin activity appeared at 3 days after operation. All indicators returned to normal at 7 days after operation. The 1-,2-,and 3-year overall survival rates were 95.5% in LDLT group and 93.5% in the technically mature SLT group, and the difference was not statistically significant. The 1-,2-,and 3-year overall survival rates were 90.2% in the early SLT group and 93.5% in the technically mature SLT group, and there was no significant difference between the two groups(P>0.05). The main complications of the early SLT group were surgery-related complications(28.1%,9/32), and the main complications of the technically mature SLT group were non-surgery-related complications(21.9%,7/32). There were 5 deaths in the SLT group,including 4 in the early SLT group and 1 in the technically mature SLT group. Conclusion: The survival rate of SLT in the treatment of biliary atresia is comparable to that of LDLT.

Predicting Experimental Heats of Formation via Deep Learning with Limited Experimental Data

When it comes to predicting experimental values of molecular properties with deep learning, the key problem is the lack of sufficient experimental data for training. We propose a method that consists of pretraining a graph neural network that aims to reproduce first-principles quantum mechanical results, followed by fine-tuning of a fully connected neural network against experimental results. The combined pretraining and fine-tuning model is expected to yield molecular properties close to experimental accuracy. This is made possible because first-principles quantum mechanical methods are often qualitatively correct or semiquantitatively accurate; thus, a calibration of the calculation results against high-precision but limited experiment data can improve accuracy greatly. Moreover, the method is highly efficient, as first-principles quantum mechanical calculation is bypassed. To demonstrate this, we apply the combined model to determine the experimental heats of formation of organic molecules made of H, C, O, N, or F atoms (up to 30 atoms), where mere 405 experimental data are used. The overall mean absolute error is 1.8 kcal/mol for these molecules.

[The expression level of secretory mature B cell surface antigen in primary diagnosed multiple myeloma and its clinical significance]

Objective: To explorer Secretory mature B cell surface antigen (sBCMA) expression level, changes during treatment and clinical significance in newly diagnosed MM patients. Methods: Clinical data of 158 MM patients admitted to the Department of Hematology, the First Affiliated Hospital of Soochow University from August 2018 to September 2020 were analyzed retrospectively. The concentration of sBCMA in the patients was determined by BCMA ELISA and compared with the normal range. The results were compared with clinical efficacy, age, type, R-ISS stage, renal impairment, and humoral immune function. Results: The median age of the patients was 57 (31-73 years old), 86 (54.5%) males and 72 (45.5%) females, mainly IgG type, 81 patients(51.2%). SBCMA value M(Q₁,Q₃) was 76.50 (55.50, 94.40) μg/L, 100% higher than the upper limit of normal value. According to the efficacy evaluation, the patients were divided into complete remission(CR) group, very good partial remission(VGPR) group, partial remission(PR) group and ineffiecacy group, the results showed the level of sBCMA in CR group[80.10 (58.05, 96.90) vs 15.70 (9.85, 28.65) μg/L] and VGPR group[74.60 (52.20, 93.00) vs 17.20 (13.30, 38.80) μg/L]was significantly higher than that before treatment(all P<0.001), and there was no significant difference in PR group and ineffective group before and after treatment (all P>0.05).The amount of serum intact protein M protein was positively correlated with the level of sBCMA expression in newly diagnosed patients (r=0.22, P=0.040), and there was no correlation between the proportion of bone marrow plasma cells and sBCMA expression (r=0.07, P=0.449).The correlation between sBCMA levels at initial diagnosis and MM type[IgG type, IgA type vs light chain type:(78.6±3.5), (72.4±5.4) vs (83.8±6.9)μg/L], age[≥65 vs<65 years: (73.6±5.5)vs (79.3±3.1)μg/L], R-ISS stage[stage Ⅰ, Ⅱ vs Ⅲ:(80.2±3.1) vs (69.4±6.1)μg/L], renal impairment [Creatinine clearance rate (Ccr) ≤30 vs>30 ml/min:(81.6±4.8) vs (76.5±3.4)μg/L], and high-risk karyotype[high-risk vs standard-risk:(73.6±5.7) vs (80.2±3.2)μg/L] were not associated (all P>0.05). Expression levels of sBCMA were negatively correlated with IgM levels in MM patients (r=-0.39, P=0.002) and after treatment (r=-0.25, P=0.015). Conclusions: The expression of sBCMA in MM patients is a reliable indicator of the clinical efficacy of MM and is related to the occurrence of MM immune deficiency and recovery after treatment. sBCMA can be used as a new independent marker for monitoring and predicting the efficacy of MM patients.

Development of a wide-range soft sensor for predicting wastewater BOD5 using an eXtreme gradient boosting (XGBoost) machine

In wastewater monitoring, detecting extremely high pollutant concentrations is necessary to properly calibrate the treatment process. However, existing hardware sensors have a limited linear range which may fail to measure extremely high levels of pollutants; and likewise, the conventional "soft" model sensors are not suitable for the highly-skewed data distributions either. This study developed a new soft sensor by using eXtreme Gradient Boosting (XGBoost) machine learning to 'measure' the wastewater organics (in terms of 5-day biochemical oxygen demand (BOD5)). The soft sensor was tested on influent and effluent BOD5 of two different wastewater treatment plants to validate the results. The model results showed that XGBoost can detect these extreme values better than conventional soft sensors. This new soft sensor can function using a sparse input matrix via XGBoost's sparsity awareness algorithm - which can address the limitation of the conventional soft sensor with the fallibility of supporting hardware sensors even.

[The short-term and long-term prognostic analysis in patients with chronic total occlusion acute non-ST segment elevation myocardial infarction]

Objectives: To investigate the clinical impacts of chronic total occlusion (CTO) in acute non-ST segment elevation myocardial infarction (NSTEMI) patients underwent primary percutaneous coronary intervention (PCI). Methods: A total of 2 271 acute NSTEMI patients underwent primary PCI from China Acute Myocardial Infarction Registry were enrolled in this study and divided into the CTO group and the non-CTO group according to the angiography. The primary endpoint was in-hospital mortality and mortality during a 2-year follow-up. The secondary endpoint was major adverse cardiovascular events (MACE) including revascularization, death, re-myocardial infarction, heart failure readmission, stroke and major bleeding. Results: Thirteen-point four percent of the total acute NSTEMI patients had concurrent CTO. In-hospital mortality (3.6% vs. 1.4%, P<0.01) and 2-year mortality (9.0% vs. 5.1%, P<0.01) were significantly higher in the CTO group than those in the non-CTO group, respectively. Multiple regression analyses showed that chronic obstructive pulmonary disease (HR 7.28, 95%CI 1.50-35.35, P=0.01) was an independent risk factor of in-hospital mortality, and advanced age (HR 1.04, 95%CI 1.01-1.07, P<0.01), and low levels of ejection fraction (HR 0.95, 95%CI 0.93-0.98, P<0.01) were independent risk factors of 2-year mortality. CTO (HR1.67, 95%CI 1.10-2.54, P=0.02) was an independent risk factor of revascularization, but not a risk factor of mortality. Conclusions: Although acute NSTEMI patients concurrent with CTO had higher mortality, CTO was only an independent risk factor of revascularization, but not of mortality. Advanced age and low levels of ejection fraction were independent risk factors of long-term death among acute NSTEMI patients.

Improving Density Functional Prediction of Molecular Thermochemical Properties with a Machine-Learning-Corrected Generalized Gradient Approximation

The past decade has seen an increasing interest in designing sophisticated density functional approximations (DFAs) by integrating the power of machine learning (ML) techniques. However, application of the ML-based DFAs is often confined to simple model systems. In this work, we construct an ML correction to the widely used Perdew-Burke-Ernzerhof (PBE) functional by establishing a semilocal mapping from the electron density and reduced gradient to the exchange-correlation energy density. The resulting ML-corrected PBE is immediately applicable to any real molecule and yields significantly improved heats of formation while preserving the accuracy for other thermochemical and kinetic properties. This work highlights the prospect of combining the power of data-driven ML methods with physics-inspired derivations for reaching the heaven of chemical accuracy.

DeepNCI: DFT Noncovalent Interaction Correction with Transferable Multimodal Three-Dimensional Convolutional Neural Networks

A multimodal deep learning model, DeepNCI, is proposed for improving noncovalent interactions (NCIs) calculated via density functional theory (DFT). DeepNCI is composed of a three-dimensional convolutional neural network (3D CNN) for abstracting critical and comprehensive features from 3D electron density, and a neural network for modeling one-dimensional quantum chemical properties. By merging features from two networks, DeepNCI is able to reduce the root-mean-square error of DFT-calculated NCI from 1.19 kcal/mol to ∼0.2 kcal/mol for a NCI molecular database (>1000 molecules). The representativeness of the joint features can be visualized by t-distributed stochastic neighbor embedding (t-SNE), where they can distinguish categorized NCI systems quite well. Therefore, the fused model performs better than its component networks. In addition, the 3D CNN takes electron density as inputs that are in the same range, despite the size of molecular systems, so it can promote model applicability and transferability. To clarify the applicability of DeepNCI, an application domain (AD) has been defined with merged features using the K-nearest-neighbor method. The calculations for external test sets are shown that AD can properly monitor the reliability for a prediction. The model transferability is tested with a small database of homolysis bond dissociation energy including only dozens of samples. With NCI database pretrained parameters, the same or better performance than the reported results is achieved by transfer learning. This suggests that the DeepNCI model is transferable and it may transfer to other relative tasks, which possibly can resolve some small sampling problems. The source code of DeepNCI can be freely accessed at https://github.com/wenzelee/DeepNCI.

Carrier-Envelope-Phase Modulated Currents in Scanning Tunneling Microscopy

Carrier-envelope-phase (CEP) stable optical pulses combined with state-of-the-art scanning tunneling microscopy (STM) can track and control ultrafast electronic tunneling currents. On the basis of nonequilibrium Green's function formalism, we present a time and frequency domain theoretical study of CEP-stable pulse-induced tunneling currents between an STM tip and a metal substrate. It is revealed that the experimentally observed phase shift between the maximum tunneling current and maximum electric field is caused by the third-order response to the electric field. The shift is also found to be sensitive to the duration of pulses. The tunneling process can thus be precisely manipulated by varying the phase and duration of these pulses.

[Analysis on human papillomavirus infection in 2 110 patients with cervical cancer in Henan province]

Objective: To explore human papillomavirus (HPV) infection status in 2 110 patients with cervical cancer in Henan province and analyze the main infection subtypes. Methods: A total of 2 110 patients with cervical cancer were detected for HPV subtypes by flow-through hybridization after PCR. The results were analyzed. Results: Among 2 110 patients with cervical cancer, 1 856 were detected to be HPV positive and the infection rate was 87.96%(95%CI: 86.57%-89.35%). The top six genotypes were HPV16, 58, 18, 52, 35 and 33. Single infection was the main type of infection in HPV positive cervical cancer patients (77.48%), and double infection was the second type infection(16.76%). The infection rate of HPV16 was 60.19%, occupying a predominant position in single or multiple infections. Among HPV positive cervical cancer patients, 1 599 cases were detected to be infected with high-risk subtypes and covered by nine-valence HPV vaccine, and the coverage rate reached 86.15% (1 599/1 856). Cervical cancer patients were mainly distributed in age group 40- years. The main HPV subtypes of cervical cancer patients were different among different age groups, but HPV16 subtype was in a predominant position in any age group. Conclusions: The main subtypes of HPV infection were HPV16, 58, 18, 52, 35 and 33 in cervical cancer patients in this study. The main infection type was single infection. There were more cervical cancer patients in age group 40- years.

Vibration-mediated resonant charge separation across the donor-acceptor interface in an organic photovoltaic device

Examination of a recent open-system Ehrenfest dynamics simulation suggests that a vibration-mediate resonance may play a pivotal role in the charge transfer across a donor-acceptor interface in an organic solar cell. Based on this, a concise dissipative two-level electronic system coupled to a molecular vibrational mode is proposed and solved quantum mechanically. It is found that the charge transfer is enhanced substantially when the vibrational energy quanta is equal to the electronic energy loss across the interface. This vibration-mediate resonant charge transfer process is ultrafast, occurring within 100 fs, comparable to experimental findings. The open-system Ehrenfest dynamics simulation of the two-level model is carried out, and similar results are obtained, which confirms further that the earlier open-system Ehrenfest dynamics simulation indeed correctly predicted the occurrence of the resonant charge transfer across the donor-acceptor interface.