Multi-omics blood atlas reveals unique features of immune and platelet responses to SARS-CoV-2 Omicron breakthrough infection.

Although host responses to the ancestral SARS-CoV-2 strain are well described, those to the new Omicron variants are less resolved. We profiled the clinical phenomes, transcriptomes, proteomes, metabolomes, and immune repertoires of >1,000 blood cell or plasma specimens from SARS-CoV-2 Omicron patients. Using in-depth integrated multi-omics, we dissected the host response dynamics during multiple disease phases to reveal the molecular and cellular landscapes in the blood. Specifically, we detected enhanced interferon-mediated antiviral signatures of platelets in Omicron-infected patients, and platelets preferentially formed widespread aggregates with leukocytes to modulate immune cell functions. In addition, patients who were re-tested positive for viral RNA showed marked reductions in B cell receptor clones, antibody generation, and neutralizing capacity against Omicron. Finally, we developed a machine learning model that accurately predicted the probability of re-positivity in Omicron patients. Our study may inspire a paradigm shift in studying systemic diseases and emerging public health concerns.

Electrically Oriented Antibodies on Transistor for Monitoring Several Copies of Methylated DNA.

An antibody transistor is a promising biosensing platform for the diagnosis and monitoring of various diseases. Nevertheless, the low concentration and short half-life of biomarkers require biodetection at the trace-molecule level, which remains a challenge for existing antibody transistors. Herein, we demonstrate a graphene field-effect transistor (gFET) with electrically oriented antibody probes (EOA-gFET) for monitoring several copies of methylated DNA. The electric field confines the orientation of antibody probes on graphene and diminishes the distance between graphene and methylated DNAs captured by antibodies, generating more induced charges on graphene and amplifying the electric signal. EOA-gFET realizes a limit of detection (LoD) of ∼0.12 copy µL-1, reaching the lowest LoD reported before. EOA-gFET shows a distinguishable signal for liver cancer clinical serum samples within ∼6 min, which proves its potential as a powerful tool for disease screening and diagnosis.

The construction of machine learning-based predictive models for high-quality embryo formation in poor ovarian response patients with progestin-primed ovarian stimulation.

OBJECTIVE: To explore the optimal models for predicting the formation of high-quality embryos in Poor Ovarian Response (POR) Patients with Progestin-Primed Ovarian Stimulation (PPOS) using machine learning algorithms. METHODS: A retrospective analysis was conducted on the clinical data of 4,216 POR cycles who underwent in vitro fertilization (IVF) / intracytoplasmic sperm injection (ICSI) at Sichuan Jinxin Xinan Women and Children's Hospital from January 2015 to December 2021. Based on the presence of high-quality cleavage embryos 72 h post-fertilization, the samples were divided into the high-quality cleavage embryo group (N = 1950) and the non-high-quality cleavage embryo group (N = 2266). Additionally, based on whether high-quality blastocysts were observed following full blastocyst culture, the samples were categorized into the high-quality blastocyst group (N = 124) and the non-high-quality blastocyst group (N = 1800). The factors influencing the formation of high-quality embryos were analyzed using logistic regression. The predictive models based on machine learning methods were constructed and evaluated accordingly. RESULTS: Differential analysis revealed that there are statistically significant differences in 14 factors between high-quality and non-high-quality cleavage embryos. Logistic regression analysis identified 14 factors as influential in forming high-quality cleavage embryos. In models excluding three variables (retrieved oocytes, MII oocytes, and 2PN fertilized oocytes), the XGBoost model performed slightly better (AUC = 0.672, 95% CI = 0.636-0.708). Conversely, in models including these three variables, the Random Forest model exhibited the best performance (AUC = 0.788, 95% CI = 0.759-0.818). In the analysis of high-quality blastocysts, significant differences were found in 17 factors. Logistic regression analysis indicated that 13 factors influence the formation of high-quality blastocysts. Including these variables in the predictive model, the XGBoost model showed the highest performance (AUC = 0.813, 95% CI = 0.741-0.884). CONCLUSION: We developed a predictive model for the formation of high-quality embryos using machine learning methods for patients with POR undergoing treatment with the PPOS protocol. This model can help infertility patients better understand the likelihood of forming high-quality embryos following treatment and help clinicians better understand and predict treatment outcomes, thus facilitating more targeted and effective interventions.

The association of post-embryo transfer SARS-CoV-2 infection with early pregnancy outcomes in in vitro fertilization: a prospective cohort study.

BACKGROUND: The influence of SARS-CoV-2 infection after embryo transfer on early pregnancy outcomes in in vitro fertilization or intracytoplasmic sperm injection-embryo transfer treatment remains inadequately understood. This knowledge gap endures despite an abundance of studies investigating the repercussions of preceding SARS-CoV-2 infection on early pregnancy outcomes in spontaneous pregnancies. OBJECTIVE: This study aimed to investigate the association between SARS-CoV-2 infection within 10 weeks after embryo transfer and early pregnancy outcomes in patients undergoing in vitro fertilization/intracytoplasmic sperm injection treatment. STUDY DESIGN: This prospective cohort study was conducted at a single public in vitro fertilization center in China. Female patients aged 20 to 39 years, with a body mass index ranging from 18 to 30 kg/m2, undergoing in vitro fertilization/intracytoplasmic sperm injection treatment, were enrolled between September 2022 and December 2022, with follow-up extended until March 2023. The study tracked SARS-CoV-2 infection time (≤14 days, ≤28 days, and ≤10 weeks after embryo transfer), symptoms, vaccination status, the interval between vaccination and embryo transfer, and early pregnancy outcomes, encompassing biochemical pregnancy rate, implantation rate, clinical pregnancy rate, and early miscarriage rate. The study used single-factor analysis and multivariate logistic regression to examine the association between SARS-CoV-2 infection status, along with other relevant factors, and the early pregnancy outcomes. RESULTS: A total of 857 female patients undergoing in vitro fertilization/intracytoplasmic sperm injection treatment were analyzed. In the first stage, SARS-CoV-2 infection within 14 days after embryo transfer did not have a significant negative association with the biochemical pregnancy rate (adjusted odds ratio, 0.74; 95% confidence interval, 0.51-1.09). In the second stage, SARS-CoV-2 infection within 28 days after embryo transfer had no significant association with the implantation rate (36.6% in infected vs 44.0% in uninfected group; P=.181). No statistically significant association was found with the clinical pregnancy rate after adjusting for confounding factors (adjusted odds ratio, 0.69; 95% confidence interval, 0.56-1.09). In the third stage, SARS-CoV-2 infection within 10 weeks after embryo transfer had no significant association with the early miscarriage rate (adjusted odds ratio, 0.77; 95% confidence interval, 0.35-1.71). CONCLUSION: Our study suggests that SARS-CoV-2 infection within 10 weeks after embryo transfer may not be negatively associated with the biochemical pregnancy rate, implantation rate, clinical pregnancy rate, and early miscarriage rate in patients undergoing in vitro fertilization/intracytoplasmic sperm injection treatment. It is important to note that these findings are specific to the target population of in vitro fertilization/intracytoplasmic sperm injection patients aged 20 to 39 years, without previous SARS-CoV-2 infection, and with a body mass index of 18 to 30 kg/m2. This information offers valuable insights, addressing current concerns and providing a clearer understanding of the actual risk associated with SARS-CoV-2 infection after embryo transfer.

A meta-analysis of randomized controlled studies examining the effects of sodium-glucose co-transporter-2 inhibitors on peripheral artery disease and risk of amputations.

AIM: Sodium-glucose co-transporter-2 inhibitors (SGLT-2is) are used to maintain glycaemic control as well as for their beneficial cardiovascular and renal effects in diabetes patients. However, increased risk of amputation and peripheral artery disease (PAD) have been observed with the use of some SGLT-2is. A meta-analysis was conducted to understand the effect of SGLT-2is on amputation and PAD events using data from randomized controlled trials (RCT). MATERIALS AND METHODS: A systematic literature review was conducted using Medline and Central databases for RCTs that involved the administration of SGLT-2is versus placebo/active comparators to diabetic patients. The primary outcome was amputation events and PAD. A random-effects model was used to calculate the pooled odds ratio, and subgroup analyses was performed. RESULTS: A total of 51 RCTs were included in the meta-analysis with data from 97 589 patients. Meta-analysis of the data showed that there was a significant increase in PAD risk (p = 0.04) but no significant increase in amputation risk with SGLT-2i use versus placebo/active comparators (p = 0.43). Subgroup analyses demonstrated no significant difference between SGLT-2i type, duration of treatment or patient risk factors on amputation or PAD incidence. However, length of drug treatment (> 100 weeks) was associated with a significant increase in both PAD and amputation risks in the SGLT-2i treatment groups. CONCLUSIONS: The results of the meta-analysis showed no significant association between SGLT-2i use and PAD and amputation risks in diabetic patients when used for shorter treatment durations.

Identifying symptom clusters and temporal interconnections in patients with lung tumors after CT-guided microwave ablation: A network analysis.

PURPOSE: To explore symptom clusters and interrelationships using a network analysis approach among symptoms in patients with lung tumors who underwent computed tomography (CT)-guided microwave ablation (MWA). METHODS: A longitudinal study was conducted, and 196 lung tumor patients undergoing MWA were recruited and were measured at 24 h, 48 h, and 72 h after MWA. The Chinese version of the MD Anderson Symptom Inventory and the Revised Lung Cancer Module were used to evaluate symptoms. Network analyses were performed to explore the symptom clusters and interrelationships among symptoms. RESULTS: Four stable symptom communities were identified within the networks. Distress, weight loss, and chest tightness were the central symptoms. Distress, and weight loss were also the most key bridge symptoms, followed by cough. Three symptom networks were temporally stable in terms of symptom centrality, global connectivity, and network structure. CONCLUSION: Our findings identified the central symptoms, bridge symptoms, and the stability of symptom networks of patients with lung tumors after MWA. These network results will have important implications for future targeted symptom management intervention development. Future research should focus on developing precise interventions for targeting central symptoms and bridge symptoms to promote patients' health.

Can Machine Learning Models Based on Computed Tomography Radiomics and Clinical Characteristics Provide Diagnostic Value for Epstein-Barr Virus-Associated Gastric Cancer?

OBJECTIVE: The aim of this study was to explore whether machine learning model based on computed tomography (CT) radiomics and clinical characteristics can differentiate Epstein-Barr virus-associated gastric cancer (EBVaGC) from non-EBVaGC. METHODS: Contrast-enhanced CT images were collected from 158 patients with GC (46 EBV-positive, 112 EBV-negative) between April 2018 and February 2023. Radiomics features were extracted from the volumes of interest. A radiomics signature was built based on radiomics features by the least absolute shrinkage and selection operator logistic regression algorithm. Multivariate analyses were used to identify significant clinicoradiological variables. We developed 6 ML models for EBVaGC, including logistic regression, Extreme Gradient Boosting, random forest (RF), support vector machine, Gaussian Naive Bayes, and K-nearest neighbor algorithm. The area under the receiver operating characteristic curve (AUC), the area under the precision-recall curves (AP), calibration plots, and decision curve analysis were applied to assess the effectiveness of each model. RESULTS: Six ML models achieved AUC of 0.706-0.854 and AP of 0.480-0.793 for predicting EBV status in GC. With an AUC of 0.854 and an AP of 0.793, the RF model performed the best. The forest plot of the AUC score revealed that the RF model had the most stable performance, with a standard deviation of 0.003 for AUC score. RF also performed well in the testing dataset, with an AUC of 0.832 (95% confidence interval: 0.679-0.951), accuracy of 0.833, sensitivity of 0.857, and specificity of 0.824, respectively. CONCLUSIONS: The RF model based on clinical variables and Rad_score can serve as a noninvasive tool to evaluate the EBV status of gastric cancer.

Plastome structure, phylogeny and evolution of plastid genes in Reevesia (Helicteroideae, Malvaceae).

Reevesia is an eastern Asian-eastern North American disjunction genus in the family Malvaceae s.l. and comprises approximately 25 species. The relationships within the genus are not well understood. Here, 15 plastomes representing 12 Reevesia species were compared, with the aim of better understanding the species circumscription and phylogenetic relationships within the genus and among genera in the family Malvaceae s.l. The 11 newly sequenced plastomes range between 161,532 and 161, 945 bp in length. The genomes contain 114 unique genes, 18 of which are duplicated in the inverted repeats (IRs). Gene content of these plastomes is nearly identical. All the protein-coding genes are under purifying selection in the Reevesia plastomes compared. The top ten hypervariable regions, SSRs, and the long repeats identified are potential molecular markers for future population genetic and phylogenetic studies. Phylogenetic analysis based on the whole plastomes confirmed the monophyly of Reevesia and a close relationship with Durio (traditional Bombacaceae) in subfamily Helicteroideae, but not with the morphologically similar genera Pterospermum and Sterculia (both of traditional Sterculiaceae). Phylogenetic relationships within Reevesia suggested that two species, R. pubescens and R. thyrsoidea, as newly defined, are not monophyletic. Six taxa, R. membranacea, R. xuefengensis, R. botingensis, R. lofouensis, R. longipetiolata and R. pycnantha, are suggested to be recognized.

Development and validation of a risk prediction model for physical frailty in older adults who are disabled.

Physical frailty is highly prevalent among the older adults who are disabled. The aim of this study was to explore the risk factors for physical frailty in older adults who are disabled and construct a nomogram prediction model. The data source was the China Health and Retirement Longitudinal Study (CHARLS). The prediction model was validated with a cohort of 1183 older adults who are disabled. The results showed that sleep quality, depression, fatigue, and chronic disease were the best predictive factors. These factors were used to construct the nomogram model, which showed good concordance and accuracy. The prediction model yielded an Area under the curve (AUC) value of 0.760. Calibration curves showed significant agreement between the nomogram model and actual observations. Receiver operating characteristic (ROC) and Decision curve analysis (DCA) showed that the nomogram had good predictive performance. The nomogram is contributed to the screening of specific populations by clinicians.

DNA Logical Computing on a Transistor for Cancer Molecular Diagnosis.

Given the high degree of variability and complexity of cancer, precise monitoring and logical analysis of different nucleic acid markers are crucial for improving diagnostic precision and patient survival rates. However, existing molecular diagnostic methods normally suffer from high cost, cumbersome procedures, dependence on specialized equipment and the requirement of in-depth expertise in data analysis, failing to analyze multiple cancer-associated nucleic acid markers and provide immediate results in a point-of-care manner. Herein, we demonstrate a transistor-based DNA molecular computing (TDMC) platform that enables simultaneous detection and logical analysis of multiple microRNA (miRNA) markers on a single transistor. TDMC can perform not only basic logical operations such as "AND" and "OR", but also complex cascading computing, opening up new dimensions for multi-index logical analysis. Owing to the high efficiency, sensing and computations of multi-analytes can be operated on a transistor at a concentration as low as 2×10-16 M, reaching the lowest concentration for DNA molecular computing. Thus, TDMC achieves an accuracy of 98.4 % in the diagnosis of hepatocellular carcinoma from 62 serum samples. As a convenient and accurate platform, TDMC holds promise for applications in "one-stop" personalized medicine.

New physics searches at kaon and hyperon factories.

Rare meson decays are among the most sensitive probes of both heavy and light new physics. Among them, new physics searches using kaons benefit from their small total decay widths and the availability of very large datasets. On the other hand, useful complementary information is provided by hyperon decay measurements. We summarize the relevant phenomenological models and the status of the searches in a comprehensive list of kaon and hyperon decay channels. We identify new search strategies for under-explored signatures, and demonstrate that the improved sensitivities from current and next-generation experiments could lead to a qualitative leap in the exploration of light dark sectors.

Artificial Nucleotide Aptamer-Based Field-Effect Transistor for Ultrasensitive Detection of Hepatoma Exosomes.

An aptamer-based field-effect transistor (Apta-FET) is a well-developed assay method with high selectivity and sensitivity. Due to the limited information density that natural nucleotide library holds, the Apta-FET faces fundamental restriction in universality to detect various types of analytes. Herein, we demonstrate a type of Apta-FET sensors based on an artificial nucleotide aptamer (AN-Apta-FET). The introduction of an artificial nucleotide increases the diversity of the potential aptamer structure and expands the analyte category of the Apta-FET. The AN-Apta-FET specifically detects hepatoma exosomes, which traditional Apta-FET fails to discriminate from other tumor-derived exosomes, with a limit of detection down to 242 particles mL-1. The AN-Apta-FET distinguishes serum samples of hepatocellular carcinoma patients within 9 min from those of healthy people, showing the potential as a comprehensive assay tool in future disease diagnosis.

Low-cost high-speed rapidly reconfigurable integrated half-duplex optical transceiver front-end.

We present and demonstrate an integrated approach to make low-cost high-speed half-duplex optical transceiver with rapid reconfigurability. A single Distributed-Feedback (DFB) diode is employed as the unified E/O-O/E device, which is dynamically biased as laser or photodetector in transmitter or receiver mode. The bias for the DFB and the transmit/receive (T/R) signal path are provided by a custom-designed reconfigurable CMOS chip, which contains the biasing circuitry, a high-speed T/R switch and a burst-mode transimpedance amplifier (BM-TIA). The transceiver front-end operates up to 5 Gb/s for both transmitter (Tx) and receiver (Rx) mode experimentally, while its reconfiguration time is less than 131 ns. This integrated approach not only halves the transceiver optics to facilitate low cost, but also enables high-speed signal transmission as well as rapid reconfiguration, which will be critical for the fiber-to-everything paradigm shift in the near future.

Impact of cervical intraepithelial neoplasia and treatment on IVF/ICSI outcomes.

STUDY QUESTION: Does treatment selection for cervical lesions affect the outcome of IVF/ICSI? SUMMARY ANSWER: There was no difference in pregnancy outcome between treated and untreated groups, or between different types of IVF/ICSI treatment. WHAT IS KNOWN ALREADY: Human papillomavirus (HPV) infection and HPV-induced cervical lesions are associated with decreased fertility, and cervical intraepithelial neoplasia (CIN) treatment may increase the risk of adverse pregnancy outcomes. STUDY DESIGN, SIZE, DURATION: Between 2018 and 2020, 190 women with infertility who had abnormal HPV screening or cytology results prior to IVF/ICSI, and were diagnosed with CIN2/CIN3 by colposcopy biopsy at a tertiary hospital, were enrolled in a retrospective cohort study with follow-up until 31 December 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS: Patients with infertility who were diagnosed with CIN2/CIN3 by colposcopy biopsy were divided into the treatment and expectant management groups. The treatment group was divided into two intervention subgroups: the ablative therapy group and the surgical treatment group. The baseline data, number of oocytes retrieved, and rates of fertilization, high-quality embryos, positive serum HCG, clinical pregnancy, abortion, live birth, and cumulative pregnancy were compared among groups. MAIN RESULTS AND THE ROLE OF CHANCE: Among the 190 patients included in the study, 152 were diagnosed with CIN2, and 38 patients had CIN3. There was no significant difference in the baseline data between the treatment and expectant groups. The time from confirmed lesions to the onset of gonadotrophin administration in the surgical treatment group was significantly longer than in the ablative therapy group and the expectant group (P = 0.007 and P = 0.024, respectively). For the treatment and expectant groups, respectively, the average number of oocytes retrieved (12.95 ± 8.77; 13.32 ± 9.16), fertilization rate (71.01 ± 23.86; 64.84 ± 26.24), and high-quality embryo rate (48.93 ± 30.72; 55.17 ± 34.13) did not differ, and no differences were detected between the different treatment subgroups. There were no differences among groups in rates of HCG positivity, clinical pregnancy, miscarriage, live birth, or cumulative pregnancy. The live birth rate in the surgical treatment group was slightly higher than that in the expectant groups (77.78% versus 66.67%), but the difference was not statistically significant. The 3-year cumulative pregnancy rates in the surgical treatment and expectant groups were 58.19% and 64.00%, respectively. LIMITATIONS, REASONS FOR CAUTION: This is a retrospective study, which by nature can include selection bias, and the number of cases in the expectant group was <30, which may result in a false-negative result owing to the small sample size. WIDER IMPLICATIONS OF THE FINDINGS: For patients with CIN2/CIN3, the treatment of cervical lesions does not affect the outcome of IVF/ICSI. Patients with CIN2 can enroll for IVF/ICSI cycles, with close follow-up to prevent the progression of cervical lesions, in order to avoid further delay in starting ART. For patients with CIN3, ovulation induction and embryo cryopreservation can be initiated as soon as possible after cervical lesions are treated, and frozen-thawed embryo transfer can be carried out 9-12 months later. STUDY FUNDING/COMPETING INTEREST(S): This work was funded by the Key Clinical Projects of the Peking University Third Hospital (to Y.W., BYSYZD2021014). The authors declare no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

Cross-Channel Constraints on Resonant Antikaon-Nucleon Scattering.

Chiral perturbation theory and its unitarized versions have played an important role in our understanding of the low-energy strong interaction. Yet, so far, such studies typically deal exclusively with perturbative or nonperturbative channels. In this Letter, we report on the first global study of meson-baryon scattering up to one-loop order. It is shown that covariant baryon chiral perturbation theory, including its unitarization for the negative strangeness sector, can describe meson-baryon scattering data remarkably well. This provides a highly nontrivial check on the validity of this important low-energy effective field theory of QCD. We show that the K[over ¯]N related quantities can be better described in comparison with those of lower-order studies, and with reduced uncertainties due to the stringent constraints from the πN and KN phase shifts. In particular, we find that the two-pole structure of Λ(1405) persists up to one-loop order reinforcing the existence of two-pole structures in dynamically generated states.

Different Concentrations of Albumin Versus Crystalloid in Patients with Sepsis and Septic Shock: A Meta-Analysis of Randomized Clinical Trials.

OBJECTIVE: The best type of resuscitation fluids for sepsis and septic shock patients remains unclear. The aim of this study was to evaluate the efficacy of different concentrations of albumin on reducing the mortality rate of theses patients by meta-analysis. MATERIALS AND METHODS: PubMed, EMBASE, and Web of Science databases were used for screening the relevant studies. Randomized controlled trials (RCTs) were eligible if they compared the effects of albumin with crystalloid on mortality in patients with sepsis and septic shock. Data were examined and extracted by two reviewers independently. Any disagreements were resolved by consensus with or without the help from a third reviewer. Data including mortality, sample size of the patients, and resuscitation endpoints were extracted. Meta-analysis was carried based on the corresponding odds ratios with 95% confidence intervals. RESULTS: Eight studies with a total of 5124 septic patients and 3482 septic shock patients were included in this study. Compared with crystalloid, the use of albumin may represent a trend toward reduced the 90-day mortality of septic patients (OR 0.91 [0.80, 1.02]; P = .11) and significantly improved the outcome of septic shock patients (OR 0.85 [0.74, 0.99]; P = .04). Further analysis showed a potentially beneficial role of both 4% to 5% and 20% albumin on reducing the mortality of septic patients. The use of 20% albumin significantly decreased the 90-day mortality of septic shock patients (OR 0.81 [0.67, 0.98]; P = .03), which was better than 4% to 5% albumin and crystalloid. CONCLUSIONS: Albumin treatment, particularly 20% albumin, significantly reduced the 90-day mortality in septic shock patients. Both 4% to 5% and 20% of albumin may work better than crystalloid in improving the survival rate of patients with sepsis, but more relative RCTs are required for validation.

Effect of serum progesterone on human chorionic gonadotropin trigger day / metaphase II oocyte ratio on pregnancy and neonatal outcomes in women undergoing ICSI cycle.

BACKGROUND: The serum progesterone on human chorionic gonadotropin trigger day / metaphase II oocyte (P/MII) ratio might be a more predictable indicator of pregnancy and neonatal outcomes as compare to P/estradiol (E2) or P alone. Hence, we conducted a larger population study to compare the pregnancy and neonatal outcomes in the low and high P/MII ratio. METHODS: A retrospective, single-center, larger population cohort study between January 2015 and August 2021. Calculate the threshold effect of P/MII ratio on clinical pregnancy rate according to the construct smooth curve fitting. Divide data into two groups by threshold for comparison. RESULTS: 3566 fresh ICSI-ET cycles were included, in which 929 singleton delivery and 676 twin deliveries. Compare to P/MII ≤ 0.367 group, it indicated that the P/MII > 0.367 group had a lower clinical pregnancy rate and live birth rate, furthermore, a significantly higher rate of LBW and SGA were observed in the singleton and twin deliveries. No deleterious impact of high P/MII ratio on embryo quality and undesirable pregnancy outcomes was shown. CONCLUSIONS: When P/MII is higher than 0.367, may have adverse impacts on pregnancy and neonatal outcomes for ICSI cycle.

Detection and Classification of Cotton Foreign Fibers Based on Polarization Imaging and Improved YOLOv5.

It is important to detect and classify foreign fibers in cotton, especially white and transparent foreign fibers, to produce subsequent yarn and textile quality. There are some problems in the actual cotton foreign fiber removing process, such as some foreign fibers missing inspection, low recognition accuracy of small foreign fibers, and low detection speed. A polarization imaging device of cotton foreign fiber was constructed based on the difference in optical properties and polarization characteristics between cotton fibers. An object detection and classification algorithm based on an improved YOLOv5 was proposed to achieve small foreign fiber recognition and classification. The methods were as follows: (1) The lightweight network Shufflenetv2 with the Hard-Swish activation function was used as the backbone feature extraction network to improve the detection speed and reduce the model volume. (2) The PANet network connection of YOLOv5 was modified to obtain a fine-grained feature map to improve the detection accuracy for small targets. (3) A CA attention module was added to the YOLOv5 network to increase the weight of the useful features while suppressing the weight of invalid features to improve the detection accuracy of foreign fiber targets. Moreover, we conducted ablation experiments on the improved strategy. The model volume, mAP@0.5, mAP@0.5:0.95, and FPS of the improved YOLOv5 were up to 0.75 MB, 96.9%, 59.9%, and 385 f/s, respectively, compared to YOLOv5, and the improved YOLOv5 increased by 1.03%, 7.13%, and 126.47%, respectively, which proves that the method can be applied to the vision system of an actual production line for cotton foreign fiber detection.

[Tonglong Kaibi Prescription for the treatment of severe benign prostate hyperplasia: A clinical study].

OBJECTIVE: To evaluate the clinical effect of the traditional Chinese medicine (TCM) Tonglong Kaibi Prescription (TKP) in the treatment of severe BPH with kidney deficiency and blood stasis combined with damp heat syndrome. METHODS: We randomly divided 120 cases of severe BPH with kidney deficiency and blood stasis combined with damp heat syndrome into three groups of equal number, treated with TKP, doxazosin mesylate sustained-release tablets (the DM control), and TKP + DM, all for 8 weeks. We obtained the IPSS, TCM symptoms scores, quality of life (QOL) scores, maximum urinary flow rate (Qmax) and postvoid residual urine volume (PVR) from the patients before and after treatment and compared them among the three groups. RESULTS: After 8 weeks of treatment, the effectiveness rate was significantly higher in the TKP + DM than in the DM control group (P < 0.05). The IPSS, TCM symptoms scores, QOL scores and PVR decreased (P < 0.01), while the Qmax increased dramatically (P < 0.01) in all the three groups. Pairwise comparison showed that the IPSS and QOL scores were lower in the TKP + DM than in the TKP and DM control groups (P < 0.05 or 0.01), and so were the TCM syndrome scores in the TKP + DM and TKP groups than in the DM control (P < 0.01). There were no statistically significant differences in PVR and Qmax among the three groups after treatment (P> 0.05), and no serious adverse events during the treatment. CONCLUSION: TKP is safe and effective in the treatment of severe BPH, which can improve the TCM symptoms, reduce the IPSS, QOL scores and PVR and increase the Qmax of the patients. TKP is evidently superior to DM alone in improving TCM symptoms of BPH and combined medication of TKP and DM produces even better clinical efficacy.

Accurate Relativistic Chiral Nucleon-Nucleon Interaction up to Next-to-Next-to-Leading Order.

We construct a relativistic chiral nucleon-nucleon interaction up to the next-to-next-to-leading order in covariant baryon chiral perturbation theory. We show that a good description of the np phase shifts up to T_{lab}=200 MeV and even higher can be achieved with a χ[over ˜]^{2}/d.o.f. less than 1. Both the next-to-leading-order results and the next-to-next-to-leading-order results describe the phase shifts equally well up to T_{lab}=200 MeV, but for higher energies, the latter behaves better, showing satisfactory convergence. The relativistic chiral potential provides the most essential inputs for relativistic ab initio studies of nuclear structure and reactions, which has been in need for almost two decades.