Glomerular filtration rate and comorbidity factors in elderly hospitalizations

BACKGROUND With an increase in the elderly population,the frequency of hospitalizations in recent years has also risen at a rapid pace.This,in turn,has resulted in poor outcomes and costly treatments.Hospitalization rates increase in elderly patients due to a decline in glomerular filtration rate(GFR).AIM To investigate the connection between GFR and comorbidity and reasons for hospitalization in elderly patients.METHODS We analyzed patients aged 75 years and over who were admitted to the internal medicine clinic of a tertiary hospital in Eskisehir.At admission,we calculated GFR values using the Modification of Diet in Renal Disease study formula and classified them into six categories:G1,G2,G3a,G3b,G4,and G5.We analyzed associations with hospitalization diagnoses and comorbidity factors.RESULTS The average age of the patients was 80.8 years(±4.5 years).GFR was 57.287±29.5 mL/kg/1.73 m2 in women and 61.3±31.5 mL/kg/1.73 m2 in men(P=0.106).Most patients were admitted to the hospital at G2 stage(32.8%).The main reasons for hospitalization were anemia(34.4%and 28.6%)and malnutrition(20.9%and 20.8%)in women and men,respectively(P=0.078).The most frequent comor-bidity leading to hospitalization was arterial hypertension(n=168,28%),fo-llowed by diabetes(n=166,27.7%)(P=0.001).CONCLUSION When evaluating geriatric patients,low GFR alone does not provide sufficient information.Patients’comorbid factors should also be taken into account.There is no association between low GFR during hospitalization and hospitalization-Hamarat H.Aging and GFR related diagnoses.Knowing the GFR value before hospitalization will be more informative in such studies.

Text-and-Timbre-Based Speech Semantic Coding for Ultra-Low-Bitrate Communications

To address the contradiction between the explosive growth of wireless data and the limited spectrum resources,semantic communication has been emerging as a promising communication paradigm.In this paper,we thus design a speech semantic coded communication system,referred to as Deep-STS(i.e.,Deep-learning based Speech To Speech),for the lowbandwidth speech communication.Specifically,we first deeply compress the speech data through extracting the textual information from the speech based on the conformer encoder and connectionist temporal classification decoder at the transmitter side of Deep-STS system.In order to facilitate the final speech timbre recovery,we also extract the short-term timbre feature of speech signals only for the starting 2s duration by the long short-term memory network.Then,the Reed-Solomon coding and hybrid automatic repeat request protocol are applied to improve the reliability of transmitting the extracted text and timbre feature over the wireless channel.Third,we reconstruct the speech signal by the mel spectrogram prediction network and vocoder,when the extracted text is received along with the timbre feature at the receiver of Deep-STS system.Finally,we develop the demo system based on the USRP and GNU radio for the performance evaluation of Deep-STS.Numerical results show that the ac-Received:Jan.17,2024 Revised:Jun.12,2024 Editor:Niu Kai curacy of text extraction approaches 95%,and the mel cepstral distortion between the recovered speech signal and the original one in the spectrum domain is less than 10.Furthermore,the experimental results show that the proposed Deep-STS system can reduce the total delay of speech communication by 85%on average compared to the G.723 coding at the transmission rate of 5.4 kbps.More importantly,the coding rate of the proposed Deep-STS system is extremely low,only 0.2 kbps for continuous speech communication.It is worth noting that the Deep-STS with lower coding rate can support the low-zero-power speech communication,unveiling a new era in ultra-efficient coded communications.

Effect of comprehensive perioperative nursing on pain intensity,complication rates,and comfort levels in patients undergoing gallstone surgery

BACKGROUND Surgery is the gold standard for gallstone treatment.Nevertheless,the complications associated with the surgical procedure can exert diverse and adverse impacts on patients’health and quality of life to varying extents.Hence,it is essential to offer perioperative care to patients undergoing gallstone surgery.AIM To examine the impact of perioperative comprehensive nursing on pain intensity,complication rates,and patient comfort in individuals undergoing gallstone surgery.METHODS From February 2022 to February 2024,195 patients who underwent gallstone surgery at Sanmen People’s Hospital were selected and divided into two groups:A control group receiving routine nursing care(95 patients)and a research group receiving perioperative comprehensive nursing(100 patients).Key postoperative recovery indicators,including time to first postoperative anal exhaust,oral food intake,and ambulation,were observed,along with pain intensity(measured by the numeric rating scale),complication rate(bleeding,incision infection,recurrence),patient comfort(assessed using the visual analogue scale),and quality of life(measured by the World Health Organization Quality of Life-BREF).RESULTS The research group showed significantly shorter times to first postoperative anal exhaust,oral intake,and ambulation.Moreover,numeric rating scale pain scores in the research group were markedly lower post-nursing,and the total complication rate was significantly reduced compared to the control group.Furthermore,comfort levels improved considerably in the research group,and World Health Organization Quality of Life-BREF scores across the physical,psychological,social,and environmental domains were significantly higher compared to the control group following nursing care.CONCLUSION Perioperative comprehensive nursing effectively enhances postoperative recovery in patients undergoing gallstone surgery,reducing pain,lowering complications,and improving patient comfort and quality of life,which deserves clinical application.

Longitudinal assessment of measured and estimated glomerular filtration-rate in autosomal dominant polycystic kidney disease:Real practice experience

BACKGROUND Equations for estimation glomerular filtration rate(eGFR)have been associated with poor clinical performance and their clinical accuracy and reliability have been called into question.AIM To assess the longitudinal changes in measured glomerular filtration rate(mGFR)in patients with autosomal dominant polycystic kidney disease(ADPKD).METHODS Analysis of an ambispective data base conducted on consecutive patients diagnosed with ADPKD.The mGFR was assessed by iohexol clearance;while eGFR was calculated by three different formulas:(1)The chronic kidney disease epidemiology collaboration(CKD-EPI);(2)Modification of diet in renal disease(MDRD);and(3)The 24-hour urine creatinine clearance(CrCl).The primary end-points were the mean change in mGFR between the baseline and final visit,as well as the comparison of the mean change in mGFR with the change estimated by the different formulas.RESULTS Thirty-seven patients were included in the study.As compared to baseline,month-6 mGFR was significantly decrease by-4.4 mL/minute±10.3 mL/minute(P=0.0132).However,the CKD-EPI,MDRD,and CrCl formulas underestimated this change by 48.3%,89.0%,and 45.8%respectively,though none of these differences reached statistical significance(P=0.3647;P=0.0505;and P=0.736,respectively).The discrepancies between measured and estimated glomerular filtration rate values,as evaluated by CKD-EPI(r=0.29,P=0.086);MDRD(r=0.19,P=0.272);and CrCl(r=0.09,P=0.683),were not correlated with baseline mGFR values.CONCLUSION This study indicated that eGFR inaccurately reflects the decline in mGFR and cannot reliably track changes over time.This poses significant challenges for clinical decision-making,particularly in treatment strategies.

Reverse effect of curcumin on CDDP-induced drug-resistance via Keap1/p62-Nrf2 signaling in A549/CDDP cell

Objective: To assess the effect of curcumin on CDDP-induced drug resistance and explore the underlying molecular mechanism through Nrf2 system and autophagy pathway.Methods: A drug-resistant cell model was established by exposing A549/CDDP cell to2 μg/mL CDDP. A549/CDDP cell was treated with 20 μg/mL CDDP and 10 μM curcumin. The cell viability and apoptosis level, the signals of Keap1/P62-Nrf2 and autophagy pathway were analyzed.Results: CDDP induction promoted drug-resistant phenotype in A549/CDDP cell and activated autophagy as well as Nrf2 signals in A549/CDDP cell. Meanwhile, curcumin combination attenuated autophagy and Nrf2 activation induced by CDDP, and reversed the drug-resistant phenotype. Notably, curcumin combination augmented Keap1 transcription. Furthermore, Keap1 ablation with short hairpin RNAs hampered the efficacy of curcumin, suggesting Keap1 played a crucial role on reversal effect of curcumin.Conclusions: The present findings demonstrate that CDDP promotes abnormal activation of Nrf2 pathway and autophagy, leading to drug resistance of A549/CDDP cell.Curcumin attenuates this process and combat drug-resistance through its potent activation on Keap1 transcription, which is essential for interplay between oxidative stress induced Nrf2 activation and autophagy/apoptosis switch.

Comparison of extended spectrum β-lactamasesproducing Escherichia coli with non-ESBLsproducing E.coli:drug-resistance and virulence

The virulent factors of Escherichia coil （E.cofi） play an important role in the process of pathopoiesis. The study aimed to compare drug-resistant genes and virulence genes between extended spectrum β-1actamases （ESBLs）-producing E.coli and non-ESBLs-producing E.cofi to provide a reference for physicians in management of hospital infection. From October 2010 to August 2011,96 drug-resistant strains of E. coli isolated were collected from the specimens in Qingdao Municipal Hospital, Qingdao, China. These bacteria strains were divided into a ESBLs-producing group and a non-ESBLs-producing group. Drug sensitivity tests were performed using the Kirby-Bauer （K-B） method. Disinfectant gene, qacEAl-sull and 8 virulence genes （CNF2, hlyA, eaeA, VT1, est, bfpA, elt, and CNF1） were tested by polymerase chain reaction （PCR）. Among the 96 E.coli isolates, the ESBLs-producing E.coli comprised 46 （47.9%） strains and the non-ESBLs-producing E.cofi consisted of 50 （52.1%） strains. The detection rates of multiple drug-resistant strain, qacEAl-sull, CNF2, hlyA, eaeA,VT1, est, bfpA, elt, and CNF1 in 46 ESBLs-producing E.coli isolates were 89.1%, 76.1%, 6.5%, 69.6%, 69.6%, 89.1%, 10.9%, 26.1%, 8.7%, and 19.6%, respectively. In the non-ESBLs-producing E.cofi strains, the positive rates of multiple drug-resistant strain, qacEAl-sull, CNF2, hlyA, eaeA, VT1, est, bfpA, elt, and CNF1 were 62.0%, 80.0%, 16.0%, 28.0%, 64.0%, 38.0%, 6.0%, 34.0%, 10.0%, and 24.0%, respectively. The difference in the detection rates of multiple drug-resistant strain, hlyA and VT1 between the ESBLs-producing E.cofi strains and the non-ESBLs-producing E.cofi strains was statistically significant （P〈0.05）. The positive rate of multiple drug-resistant strains is higher in the ESBLs-producing strains than in the non-ESBLs-producing strains. The expression of some virulence genes hlyA and VT1 varies between the ESBLs-producing strains and the non-ESBLs-producing strains. Increased awareness of clinicians and enhanced testing by laboratories are required to reduce treatment failures and prevent the spread of multiple drug-resistant strains.

Three-dimensional collagen-based scaffold model to study the microenvironment and drug-resistance mechanisms of oropharyngeal squamous cell carcinomas

Objective:Squamous cell carcinoma(SCC)represents the most common histotype of all head and neck malignancies and includes oropharyngeal squamous cell carcinoma(OSCC),a tumor associated with different clinical outcomes and linked to human papilloma virus(HPV)status.Translational research has few available in vitro models with which to study the different pathophysiological behavior of OSCCs.The present study proposes a 3-dimensional(3 D)biomimetic collagen-based scaffold to mimic the tumor microenvironment and the crosstalk between the extracellular matrix(ECM)and cancer cells.Methods:We compared the phenotypic and genetic features of HPV-positive and HPV-negative OSCC cell lines cultured on common monolayer supports and on scaffolds.We also explored cancer cell adaptation to the 3 D microenvironment and its impact on the efficacy of drugs tested on cell lines and primary cultures.Results:HPV-positive and HPV-negative cell lines were successfully grown in the 3 D model and displayed different collagen fiber organization.The 3 D cultures induced an increased expression of markers related to epithelial–mesenchymal transition(EMT)and to matrix interactions and showed different migration behavior,as confirmed by zebrafish embryo xenografts.The expression of hypoxia-inducible factor 1α(1α)and glycolysis markers were indicative of the development of a hypoxic microenvironment inside the scaffold area.Furthermore,the 3 D cultures activated drug-resistance signaling pathways in both cell lines and primary cultures.Conclusions:Our results suggest that collagen-based scaffolds could be a suitable model for the reproduction of the pathophysiological features of OSCCs.Moreover,3 D architecture appears capable of inducing drug-resistance processes that can be studied to better our understanding of the different clinical outcomes of HPV-positive and HPV-negative patients with OSCCs.

Molecular Characterization and Drug-resistance of Mycobacterium tuberculosis Strains in Xuzhou, China

To understand the genetic diversity and drug resistance status of Mycobocterium tuberculosis （M. tuberculosis） circulating in Xuzhou of China, the spacer-oligonucleotide typing （Spoligotyping） and multi-loci VNTRs （variable number tandem repeats） analysis （MLVA） were utilized for the genotyping of the isolates. Drug susceptibility test （DST） was performed by the proportion method on the Lowenstein-Jensen （L-J） medium using isoniazid, rifampicin, ethambutol, and streptomycin. By Spoligotyping, 287 M. tuberculosis isolates were differentiated into 14 clusters. Then with 15-1oci MLVA, these strains could be divided into 32 clusters, 228 genotypes. Of 15 VNTRs, 6 loci had the highly discriminatory powers, 6 loci presented moderate discrimination and 3 loci demonstrated less polymorphism. The DST results showed that 46 strains were resistant to at least one first-line anti-tuberculosis agent. There was a difference in the isoniazid resistance between Beijing and non-Beijing genotype strains. We concluded that the combination of Spoligotyping and 15 VNTR loci as the genotyping in our study was applicable for this region, the drug resistant isolates were identified, and the Beijing family was the most prevalent genotype in the rural counties of Xuzhou.

Treatment strategies and preventive methods for drug-resistant Helicobacter pylori infection

The infection and drug resistance rates of Helicobacter pylori(H.pylori)are high and must be prevented and treated by better strategies.Based on recent research advances in this field as well as the results from our team and those on traditional Chinese medicine,we review the causes of drug resistance,and prevention and treatment strategies for drug-resistant H.pylori infection,with an aim to make suggestions for the development of new drugs,such as establishment of new target identification and screening systems,modification of existing drug structures,use of new technologies,application of natural products,and using a commercial compound library.This article may provide reference for eradication of drug-resistant H.pylori.

Investigation of immune escape-associated mutations of hepatitis B virus in patients harboring hepatitis B virus drug-resistance mutations

It is unclear whether immune escape-associated mutations in the major hydrophilic region of hepatitis B virus surface antigen(HBsAg)are associated with nucleoside/nucleotide analog resistance.AIM To evaluate the association between immune escape-associated mutations and nucleoside/nucleotide analog resistance mutations.METHODS In total,19440 patients with chronic hepatitis B virus infection,who underwent resistance testing at the Fifth Medical Center of Chinese PLA General Hospital between July 2007 and December 2017,were enrolled.As determined by sequence analysis,6982 patients harbored a virus with resistance mutations and 12458 harbored a virus lacking resistance mutations.Phenotypic analyses were performed to evaluate HBsAg production,replication capacity,and drug-induced viral inhibition of patient-derived drug-resistant mutants with or without the coexistence of sA159V.RESULTS The rate of immune escape-associated mutation was significantly higher in 9 of the 39 analyzed mutation sites in patients with resistance mutations than in patients without resistance mutations.In particular,these mutations were sQ101H/K/R,sS114A/L/T,sT118A/K/M/R/S/V,sP120A/L/Q/S/T,sT/I126A/N/P/S,sM133I/L/T,sC137W/Y,sG145A/R,and sA159G/V.Among these,sA159V was detected in 1.95%(136/6982)of patients with resistance mutations and 1.08%(134/12,458)of patients lacking resistance mutations(P<0.05).The coexistence of sA159V with lamivudine(LAM)and entecavir(ETV)-resistance mutations in the same viral genome was identified during follow-up in some patients with drug resistance.HBsAg production was significantly lower and the replication capacity was significantly higher,without a significant difference in LAM/ETV susceptibility,in sA159V-containing LAM/ETV-resistant mutants than in their sA159V-lacking counterparts.CONCLUSION In summary,we observed a close link between the increase in certain immune escape-associated mutations and the development of resistance mutations.sA159V might increase the fitness of LAM/ETV-resistant mutants under environmental pressure in some cases.

Prediction model for corrosion rate of low-alloy steels under atmospheric conditions using machine learning algorithms

This work constructed a machine learning(ML)model to predict the atmospheric corrosion rate of low-alloy steels(LAS).The material properties of LAS,environmental factors,and exposure time were used as the input,while the corrosion rate as the output.6 dif-ferent ML algorithms were used to construct the proposed model.Through optimization and filtering,the eXtreme gradient boosting(XG-Boost)model exhibited good corrosion rate prediction accuracy.The features of material properties were then transformed into atomic and physical features using the proposed property transformation approach,and the dominant descriptors that affected the corrosion rate were filtered using the recursive feature elimination(RFE)as well as XGBoost methods.The established ML models exhibited better predic-tion performance and generalization ability via property transformation descriptors.In addition,the SHapley additive exPlanations(SHAP)method was applied to analyze the relationship between the descriptors and corrosion rate.The results showed that the property transformation model could effectively help with analyzing the corrosion behavior,thereby significantly improving the generalization ability of corrosion rate prediction models.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

Dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates

Interactive holography offers unmatched levels of immersion and user engagement in the field of future display.Despite of the substantial progress has been made in dynamic meta-holography,the realization of real-time,highly smooth interactive holography remains a significant challenge due to the computational and display frame rate limitations.In this study,we introduced a dynamic interactive bitwise meta-holography with ultra-high computational and display frame rates.To our knowledge,this is the first reported practical dynamic interactive metasurface holographic system.We spa-tially divided the metasurface device into multiple distinct channels,each projecting a reconstructed sub-pattern.The switching states of these channels were mapped to bitwise operations on a set of bit values,which avoids complex holo-gram computations,enabling an ultra-high computational frame rate.Our approach achieves a computational frame rate of 800 kHz and a display frame rate of 23 kHz on a low-power Raspberry Pi computational platform.According to this methodology,we demonstrated an interactive dynamic holographic Tetris game system that allows interactive gameplay,color display,and on-the-fly hologram creation.Our technology presents an inspiration for advanced dynamic meta-holography,which is promising for a broad range of applications including advanced human-computer interaction,real-time 3D visualization,and next-generation virtual and augmented reality systems.

INTERFACE BEHAVIOR AND DECAY RATES OF COMPRESSIBLE NAVIER-STOKES SYSTEM WITH DENSITY-DEPENDENT VISCOSITY AND A VACUUM

In this paper,we study the one-dimensional motion of viscous gas near a vacuum,with the gas connecting to a vacuum state with a jump in density.The interface behavior,the pointwise decay rates of the density function and the expanding rates of the interface are obtained with the viscosity coefficientμ(ρ)=ρ^(α)for any 0<α<1;this includes the timeweighted boundedness from below and above.The smoothness of the solution is discussed.Moreover,we construct a class of self-similar classical solutions which exhibit some interesting properties,such as optimal estimates.The present paper extends the results in[Luo T,Xin Z P,Yang T.SIAM J Math Anal,2000,31(6):1175-1191]to the jump boundary conditions case with density-dependent viscosity.

The Probability Density Function Related to Shallow Cumulus Entrainment Rate and Its Influencing Factors in a Large-Eddy Simulation

The process of entrainment-mixing between cumulus clouds and the ambient air is important for the development of cumulus clouds.Accurately obtaining the entrainment rate(λ)is particularly important for its parameterization within the overall cumulus parameterization scheme.In this study,an improved bulk-plume method is proposed by solving the equations of two conserved variables simultaneously to calculateλof cumulus clouds in a large-eddy simulation.The results demonstrate that the improved bulk-plume method is more reliable than the traditional bulk-plume method,becauseλ,as calculated from the improved method,falls within the range ofλvalues obtained from the traditional method using different conserved variables.The probability density functions ofλfor all data,different times,and different heights can be well-fitted by a log-normal distribution,which supports the assumed stochastic entrainment process in previous studies.Further analysis demonstrate that the relationship betweenλand the vertical velocity is better than other thermodynamic/dynamical properties;thus,the vertical velocity is recommended as the primary influencing factor for the parameterization ofλin the future.The results of this study enhance the theoretical understanding ofλand its influencing factors and shed new light on the development ofλparameterization.

Experimental study on the effect of unloading rate on gneiss rockburst

Rockburst are often encountered in tunnel construction due to the complex geological conditions.To study the influence of unloading rate on rockburst,gneiss rockburst experiments were conducted under three groups of unloading rates.A high-speed photography system and acoustic emission(AE)system were used to monitor the entire process of rockburst process in real-time.The results show that the intensity of gneiss rockburst decreases with decrease of unloading rate,which is manifested as the reduction of AE energy and fragments ejection velocity.The mechanisms are proposed to explain this effect:(i)The reduction of unloading rate changes the crack propagation mechanism in the process of rockburst.This makes the rockbursts change from the tensile failure mechanism at high unloading rate to the tension-shear mixed failure mechanism at low unloading rate,and more energy released in the form of shear crack propagation.Then,less strain energy is converted into kinetic energy of fragments ejection.(ii)Less plate cracking degree of gneiss has taken shape due to decrease of unloading rate,resulting in the destruction of rockburst incubation process.The enlightenments of reducing the unloading rate for the project are also described quantitatively.The rockburst magnitude is reduced from the medium magnitude at the unloading rate of 0.1 MPa/s to the slight magnitude at the unloading rate of 0.025 MPa/s,which was judged by the ejection velocity.

A new era of mutation rate analyses: Concepts and methods

The mutation rate is a pivotal biological characteristic,intricately governed by natural selection and historically garnering considerable attention.Recent advances in high-throughput sequencing and analytical methodologies have profoundly transformed our understanding in this domain,ushering in an unprecedented era of mutation rate research.This paper aims to provide a comprehensive overview of the key concepts and methodologies frequently employed in the study of mutation rates.It examines various types of mutations,explores the evolutionary dynamics and associated theories,and synthesizes both classical and contemporary hypotheses.Furthermore,this review comprehensively explores recent advances in understanding germline and somatic mutations in animals and offers an overview of experimental methodologies,mutational patterns,molecular mechanisms,and driving forces influencing variations in mutation rates across species and tissues.Finally,it proposes several potential research directions and pressing questions for future investigations.

Present-day Upper-crustal Strain Rate Field in Southeastern Tibet and its Geodynamic Implications:Constraints from GPS Measurements with ABIC Method

The Earth’s surface kinematics and deformation are fundamental to understanding crustal evolution.An effective research approach is to estimate regional motion field and deformation fields based on modern geodetic networks.If the discrete observed velocity field is obtained,the velocity related fields,such as dilatation rate and maximum shear strain rate,can be estimated by applying varied mathematical approaches.This study applied Akaike's Bayesian Information Criterion(ABIC)method to calculate strain rate fields constrained by GPS observations in the southeast Tibetan Plateau.Comparison with results derived from other three methods revealed that our ABIC-derived strain rate fields were more precise.The maximum shear strain rate highlighted the Xianshuihe–Xiaojiang fault system as the main boundary for the outward migration of material in southeastern Tibet,indicating rotation of eastern Tibet material around the eastern Himalaya rather than whole extrusion along a fixed channel.Additionally,distinct dilatation rate patterns in the northeast and southwest regions of the fault system were observed.The northeast region,represented by the Longmenshan area,exhibited negative dilatational anomalies;while the southwest region,represented by the Jinsha River area north of 29°N,displayed positive dilatational anomalies.This indicates compression in the former and extension in the latter.Combined with deep geophysical observations,we believe that the upper and lower crusts of the Jinsha River area north of 29°N are in an entire expanding state,probably caused by the escape-drag effect of material.The presence of a large,low-viscosity region south of 29°N may not enable the entire escape of the crust,but instead result in a differential escape of the lower crust faster than the upper crust.

Global burden of HIV-negative multidrug-and extensively drug-resistant tuberculosis based on Global Burden of Disease Study 2021

Background:Tuberculosis(TB),caused by Mycobacterium tuberculosis,remains the second leading cause of death from a single infectious disease globally and poses a significant economic and clinical burden in the world in 2022.Of particular concern is the emergence of drug-resistant TB,accounting for 15%-20%of TB deaths.It is imperative to delve into the global trends of incidence and death rate for multidrug-resistant tuberculosis(MDRTB)and extensively drug-resistant tuberculosis(XDR-TB),drawing upon the comprehensive Global Burden of Disease(GBD)2021 drug-resistant tuberculosis dataset.Methods:From the GBD 2021,data on incidence,prevalence,disability-adjusted life years(DALYs),and death of MDR-TB and XDR-TB from 1990 to 2021 were collected.We calculated the estimated annual percentage changes in age standardized incidence rate(ASIR)and age-standardized death rate(ASDR),segmented by age,sex,and socio-demographic index(SDI).The impacts of various risk factors on MDR-TB and XDR-TB were also analyzed.Results:In 2021,there were an estimated 443,680(95%uncertainty interval[UI]:259,196-766,545)incident cases of MDR-TB,and an estimated 106,818(95%UI:41,612-211,854)death cases of MDR-TB,while there were an estimated 24,036(95%UI:17,144-34,587)incident cases of XDR-TB and 7,946(95%UI:3,326-14,859)death cases of XDR-TB.The incidence and death cases of MDR-TB were lowest in high SDI regions,whereas the incidence rates of XDR-TB in high-middle SDI regions were higher than those in middle SDI and high SDI regions.Conclusion:This study reported the disease burden of drug-resistant TB from 1990 to 2021.Until 2021,drugresistant TB is still a serious problem in low SDI countries,especially for high-risk age populations with highrisk factors.Controlling drug-resistant TB requires effective control strategies and healthcare systems.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.