Scale Reduction Research Articles

Analisis Penerapan Etika Bisnis Islam dalam Transaksi Jual Beli Ikan Basah di Pasar Simpang Tiga Kecamatan Luhak Nan Duo Kabupaten Pasaman Barat

This research aims to find out how the application of Islamic business ethics in buying and selling transactions by wet fish traders in the Simpang Tiga market. This research uses descriptive qualitative research methods. This type of descriptive qualitative research is research where the aim is to provide descriptions of a fact, and properties related to the phenomenon being studied. This qualitative research has the aim of producing data in the form of oral words and how behavior is being observed. This research was conducted through direct observation and interviews with market managers as well as fish traders and fish buyers in the Simpang Tiga market, Luhak Nan Duo District, West Pasaman Regency. The results of this study are the implementation of buying and selling wet fish in the Simpang Tiga market carried out by traders on Friday at 07.00 to 18.00. At the time of the implementation of the transaction of buying and selling wet fish, there are still many traders who leave Friday prayers in order to continue trading and cheating by reducing the scales where the average reduction in scales is 0.10-0.15kg. The review of Islamic business ethics in the implementation of buying and selling wet fish in the Simpang Tiga market is not in accordance with the principles of Islamic business ethics, such as the principle of oneness (tawhid), the principle of justice, the principle of honesty, the principle of responsibility and the principle of freedom. The fraud committed by traders aims to get more profit.

Potensi Air Kelapa Hijau Dan Kompres Hangat Dalam Mengatasi Dismenore Primer Pada Remaja Putri: Studi Di PMB S Tahun 2023

Based on adolescent report from Pandeglang Regency Health Office, there are 1178 cases of menstrual disorders in adolescents. Based on adolescent program report at UPTD Puskesmas Cikeusik until November 2022, 43.5% of adolescents experience dysmenorrhea or menstrual disorders. The impact of dysmenorrhea causes discomfort, difficulty concentrating in learning and decreased motivation to learn because of the pain felt, can limit women to carry out daily activities so that the need for handling dysmenorrhea in adolescents. The aim is to determine the effectiveness of green coconut water on reducing primary dysmenorrhea pain in adolescent girls in 2023. The sample population in this study were 2 respondents, namely adolescents who experienced primary dysmenorrhea by comparing directly to the response of green coconut water and warm water compresses. The research time was carried out on February 6, 2024 to February 10, 2024 and February 9 to February 11, 2024. Methods Data collection methods by means of assessment, namely interviews to explore the data needed related to the research to be carried out on adolescent girls with primary dysmenorrhea. The results showed a reduction in the pain scale after being given green coconut water. Conclusion In the results of the study, significant results were obtained in reducing primary dysmenorrhea, namely drinking green coconut water 1-3 days of menstruation, because the results obtained reduced pain from scale 4 to scale 2. Suggestions It is expected to apply the green coconut water method and warm water compresses on reducing dysmenorrhea pain.

Efficacy and safety of Dyna CT-assisted percutaneous balloon compression in the treatment of tumor-related trigeminal neuralgia: A single-center retrospective analysis

BackgroundPercutaneous balloon compression (PBC) has been widely used in the treatment of trigeminal neuralgia (TN). Patients with tumor-related TN are typically treated by tumor resection. However, when craniotomy is not feasible, PBC may serve as a simple and effective method for pain relief. Currently, there is limited literature on the use of this technique in treating patients with tumor-related TN. In this study, we aim to evaluate the efficacy and safety of Dyna CT-assisted PBC in the treatment of tumor-related TN. MethodsFrom January 2018 to December 2023, a total of 19 patients with tumor-related TN underwent Dyna CT-assisted PBC at our institution. The modified Barrow Neurological Institute Pain Intensity Grading Scale and sensory reduction scores were employed to assess treatment outcomes. A retrospective analysis was conducted on the clinical characteristics, surgical efficacy, postoperative complications, and follow-up results of all patients. ResultsImmediate and complete pain relief was observed in 18 patients following PBC, with one patient experiencing delayed recovery. Follow-up periods ranged from 4 to 62 months, revealing only 4 patients with pain recurrence at the last follow-up, and tumor-related TN patients with involvement of Meckel's cave were more prone to recurrence. No severe complications occurred throughout the follow-up period. Although facial numbness was reported in all 15 patients, jaw weakness in 8 patients, and postoperative headache in 7 patients, these symptoms resolved within a short period. There were no statistically significant differences in postoperative facial numbness and jaw weakness between tumor-related TN patients with or without Meckel's cave involvement. However, patients with Meckel's cave involvement were more likely to experience postoperative headaches. Patient satisfaction scores indicated a significant improvement in postoperative quality of life. ConclusionFor patients with tumor-related TN, when craniotomy is not feasible, Dyna CT-assisted PBC proves to be a safe and effective alternative treatment. Additionally, we observed varying postoperative clinical outcomes based on the different sites of tumor compression on the trigeminal nerve. Patients with tumor-related TN not involving Meckel's cave exhibited more enduring clinical efficacy compared to those with Meckel's cave involvement.

Experimental study and turbulence dissipative scale modelling of the rapid micromixing of impinging thin sheets of liquids

Previous studies have shown that the impingement of thin liquid sheets produces high energy dissipation rates due to the release of kinetic energy in a very small mass of liquid (0.0001–0.01 g), even though flowrates are on the order of L/min. Rapid micromixing occurs because the dissipated energy leads to a substantial reduction in the initial segregation size scale of the liquids, which is the single-sheet thickness at impingement (~ 100 μm). In the present study, the micromixing was investigated by following the progress of an acid-base neutralization accompanied by a change in fluorescence intensity of a fluorophore. Micromixing was modeled using a framework that assumes diffusion and reaction of species occur within slabs of fixed thickness (2L). The slabs are fixed in size because the released kinetic energy is dissipated within one turnover time of the large energy-containing eddies produced in the turbulent impingement zone. A simulation, which included a module for calculating the fluorescence intensity, determined 2L for experimental energy dissipation rates (ϵ) ranging from 4×104 to 7.7×106 W/kg. 2L was found to lie in the range of turbulent dissipative scales less than the Taylor microscale but greater than the Kolmogorov microscale. 2L/v′ was found to be a function of ReΛ−1/4 and ν/ϵ1/2, where v′ is the velocity associated with the turbulent kinetic energy, ReΛ is the large-eddy Reynolds number and ν is the kinematic viscosity. Similar to η/Λ, 2L/Λ is a function of ReΛ−3/4, where ηis the Kolmogorov microscale and Λ is the size of the large energy-containing eddies.

Collaborative Methods of Resolving Road Graphic Conflicts Based on Cartographic Rules and Generalization Operations

The resolution of road graphic conflicts is a key aspect of map generalization, which involves both scale reduction and the symbolization of map features. This study proposes collaborative methods of road graphic conflict resolution considering different road characteristics. These methods consider both geometric and semantic characteristics, and they incorporate the bend characteristics of roads, the road symbol size, and road semantics. Constrained Delaunay triangulation skeleton lines are used to categorize road graphic conflicts, which are made up of four independent conflict types and four group conflict types. Based on their characteristics, three collaborative methods are designed to deal with the different types of road graphic conflicts: collaboration between deletion and the snake displacement model, collaboration between the snake displacement model and collinearity, and collaboration among simplification, smoothing, and the beam displacement model. Two types of independent conflicts can be processed using only one simple operation. This study summarizes the cartographic rules for resolving road graphic conflicts, and these are used along with geometric features to drive the collaborative methods or one simple operation presented here. The experimental results indicate that the method proposed in this study can effectively resolve road graphic conflicts.

Clinical effect of digitalized designed and 3D-printed repositioning splints in the treatment of anterior displacement of temporomandibular joint disc

ObjectiveTo compare the treatment effectiveness of digitized and 3D-printed repositioning splints with that of conventional repositioning splints in the treatment of anterior displacement of the temporomandibular joint disc.MethodsThis retrospective study included 96 patients with disc displacement of the anterior temporomandibular joint. They were treated with either digitally designed and 3D-printed repositioning splints or traditional splints and followed up for at least six months. Changes in signs and symptoms such as pain and mouth opening before and after treatment were recorded to evaluate treatment outcomes.ResultsDuring the first month of treatment, both the digitally designed and 3D-printed repositioning splint groups (Group B) and the traditional repositioning splint group (Group A) showed significant increases in mouth opening, with increases of 4.93 ± 3.06 mm and 4.07 ± 4.69 mm, respectively, and there was no significant difference between the two groups. Both groups had a significant reduction in visual analog scale (VAS) pain scores, with Group B showing a greater reduction of 1.946 ± 1.113 compared to 1.488 ± 0.978 in Group A (P < 0.05). By the sixth month, Group B’s mouth opening further improved to 38.65 ± 3.22 mm (P < 0.05), while Group A’s mouth opening did not significantly improve. Regarding pain, Group A’s VAS score decreased by 0.463 ± 0.778 after one month, and Group B’s score decreased by 0.455 ± 0.715; both groups showed significant reductions, but there was no significant difference between the two groups.ConclusionCompared with traditional repositioning splints, digitally designed and 3D-printed repositioning splints are more effective at reducing patient pain and improving mouth opening. 3D-printed repositioning splints are an effective treatment method for temporomandibular joint disc displacement and have significant potential for widespread clinical application.

Robotic endoscopic transforaminal lumbar interbody fusion: A single institution case series

BackgroundRobotic-assisted, endoscopic transforaminal lumbar interbody fusion (RE-TLIF) is a promising, minimally invasive surgical option for degenerative lumbar spondylosis/spondylolisthesis; however, outcomes data and efficacy are limited, especially in multilevel disease. Here, we present the first reported series of patients that underwent either single or multilevel RE-TLIF. MethodsA retrospective review was performed on 23 consecutive patients who underwent a single level or multilevel RE-TLIF by a single surgeon. Variables included demographics, perioperative results, pain scores, and functional outcome scores. ResultsEighteen patients (78.3 %) underwent single level RE-TLIF and 5 patients (21.7 %) underwent multilevel RE-TLIF. The median reduction of visual analog scale (VAS) for low back pain (LBP) of all subjects was 6 (IQR = 4.5, 6.5) with no significant difference between single level and multilevel RE-TLIF (p = 0.565). The median reduction of VAS for leg pain of all subjects 7 (IQR = 6, 8) with no significant difference between single level and multilevel RE-TLIF (p = 0.702). Median blood loss was 25 cc (IQR = 25, 25) and 50 cc (IQR = 25, 100) for single and multilevel RE-TLIF, respectively (p = 0.025), whereas median length of stay was 1 (IQR = 1, 1; mean = 1.0 ± 00.18) days and 1 (IQR = 1, 2; mean = 1.4 ± 00.54) days, respectively (p = 0.042). One major complication was observed requiring reoperation for demineralized bone matrix migration resulting in an L5 radiculopathy. ConclusionsSingle and multi-level RE-TLIF appears to be a safe and efficacious approach with comparable outcomes to open and other minimally invasive approaches. Additionally, we observed favorable accuracy in robot-assisted pedicle screw, endoscope, and interbody device placement.

Altered Serotonin 1B Receptor Binding After Escitalopram for Depression Is Correlated With Treatment Effect.

Major depressive disorder (MDD) is commonly treated with selective serotonin reuptake inhibitors (SSRIs). SSRIs inhibit the serotonin transporter (5-HTT), but the downstream antidepressant mechanism of action of these drugs is poorly understood. The serotonin 1B (5-HT1B) receptor is functionally linked to 5-HTT and 5-HT1B receptor binding and 5-HT1B receptor mRNA is reduced in the raphe nuclei after SSRI administration in primates and rodents, respectively. The effect of SSRI treatment on 5-HT1B receptor binding in patients with MDD has not been examined previously. This positron emission tomography (PET) study aimed to quantify brain 5-HT1B receptor binding changes in vivo after SSRI treatment for MDD in relation to treatment effect. Eight unmedicated patients with moderate to severe MDD underwent PET with the 5-HT1B receptor radioligand [11C]AZ10419369 before and after 3 to 4 weeks of treatment with the SSRI escitalopram 10mg daily. Depression severity was assessed at time of PET and after 6 to 7 weeks of treatment with the Montgomery-Åsberg Depression Rating Scale. We observed a significant reduction in [11C]AZ10419369 binding in a dorsal brainstem (DBS) region containing the median and dorsal raphe nuclei after escitalopram treatment (P = .036). Change in DBS [11C]AZ10419369 binding correlated with Montgomery-Åsberg Depression Rating Scale reduction after 3-4 (r = 0.78, P = .021) and 6-7 (r = 0.94, P < .001) weeks' treatment. Our findings align with the previously reported reduction of 5-HT1B receptor binding in the raphe nuclei after SSRI administration and support future studies testing change in DBS 5-HT1B receptor binding as an SSRI treatment response marker.

Enhancing concrete durability in chloride-rich environments through manual application of healing agents

Concrete structures in chloride-rich environments are prone to deterioration, especially when ions can intrude via cracks towards the steel reinforcement. Self-healing concrete could significantly extend the service life of reinforced concrete. Hence, selecting appropriate healing agents to improve the durability is a critical challenge for the construction industry. This study investigates the use of three potential healing agents: water-repellent agent (WRA), sodium silicate (SS), and polyurethane (PU). The agents are tested separately under two conditions: exposure to a 3.3 % NaCl concentration at 20 °C and exposure to cyclic freeze-thaw conditions. The agents are manually injected into the cracks and evaluated for their healing efficiency using the capillary absorption test and microscopy analysis. Additionally, their resistance to freeze-thaw cycles by monitoring mass loss and chloride bulk diffusion is measured using sprayed silver nitrate, titration, and EDX mapping. The results demonstrate the effectiveness of PU in completely preventing chloride ingress and withstanding the freeze-thaw cycles. On the other hand, WRA showed a significant reduction in scaling, being the only healing agent to keep scaling below the appropriate scaling level of 1 kg/m2. Although WRA had the best performance in the scaling test and prevented chloride ingress, some influence was observed from the freeze-thaw cycles with regard to chloride ingress. Samples treated with SS performed better than the reference samples but did not show the same effectiveness as samples treated with PU or WRA in preventing chloride ingress. Overall, the study highlights the potential of healing agents in improving the durability of concrete structures in chloride-rich environments, with PU and WRA being the most promising for further development and optimization.

Magnetic Seizure Therapy vs Modified Electroconvulsive Therapy in Patients With Bipolar Mania

Bipolar mania is a common disabling illness. Electroconvulsive therapy (ECT) is an effective treatment for patients with severe mania, though it is limited by the risk of cognitive adverse effects. Magnetic seizure therapy (MST) as an alternative treatment to ECT for bipolar mania has not yet been reported. To compare the effectiveness and cognitive adverse effects of MST and ECT in bipolar mania. This randomized clinical trial was conducted at the Shanghai Mental Health Center from July 1, 2017, through April 26, 2021. Forty-eight patients with bipolar mania were recruited and randomly allocated to receive MST or ECT. The data analysis was performed from June 5, 2021, through August 30, 2023. Patients completed 2 or 3 sessions of MST or ECT per week for a total of 8 to 10 sessions. The MST was delivered at 100% device output with a frequency of 75 Hz over the vertex. The primary outcomes were reduction of total Young Manic Rating Scale (YMRS) score and response rate (more than 50% reduction of the total YMRS score compared with baseline). An intention-to-treat (ITT) analysis and repeated-measures analyses of variance were conducted for the primary outcomes. Twenty patients in the ECT group (mean [SD] age, 31.6 [8.6] years; 12 male [60.0%]) and 22 patients in the MST group (mean [SD] age, 34.8 [9.8] years; 15 male [68.2%]) were included in the ITT analysis. The response rates were 95.0% (95% CI, 85.4%-100%) in the ECT group and 86.4% (95% CI, 72.1%-100%) in the MST group. The YMRS reduction rate (z = -0.82; 95% CI, -0.05 to 0.10; P = .41) and response rate (χ2 = 0.18; 95% CI, -0.13 to 0.31; P = .67) were not significantly different between the groups. The time-by-group interaction was significant for the language domain (F1,24 = 7.17; P = .01), which was well preserved in patients receiving MST but worsened in patients receiving ECT. No serious adverse effects were reported in either group. These findings suggest that MST is associated with a high response rate and fewer cognitive impairments in bipolar mania and that it might be an alternative therapy for the treatment of bipolar mania. ClinicalTrials.gov Identifier: NCT03160664.

Bayesian inversion and uncertainty analysis of transient electromagnetic data

AbstractQuantification of non‐uniqueness and uncertainty is important for transient electromagnetism (TEM). To address this issue, we develop a trans‐dimensional Bayesian inversion schema for TEM data interpretation. The trans‐dimensional posterior probability density (PPD) offers a solution to model selection and quantifies parameter uncertainty resulting from the model selection from all possible models rather than determining a single model. We use the reversible‐jump Markov chain Monte Carlo sampler to draw ensembles of models to approximate PPD. In addition to providing reasonable model selection, we address the reliability of the inversion results for uncertainty analysis. This strategy offers reasonable guidance when interpreting the inversion results. We make the following improvements in this paper. First, in terms of algorithmic acceleration, we use the nonlinear optimization inversion results as the initial model and implement the multi‐chain parallel method. Second, we develop double factors to control the sampling step size of the proposed distribution, so that the sampling models cover the high‐probability region of the parameter space as much as possible. Finally, we provide the potential scale reduction factor‐η convergence criteria to assess the convergence of the samples and ensure the rationality of the output models. The proposed methodology is first tested on synthetic data and subsequently applied to a field dataset. The TEM inversion results show that probability inversion can provide reliable references for data interpretation through uncertainty analysis.

Innovative approach towards early prediction of ovarian cancer: Machine learning- enabled XAI techniques

Globally, ovarian cancer affects women disproportionately, causing significant morbidity and mortality rates. The early diagnosis of ovarian cancer is necessary for enhancing patient health and survival rates. This research article explores the utilization of Machine Learning (ML) techniques alongside eXplainable Artificial Intelligence (XAI) methodologies to aid in the early detection of ovarian cancer. ML techniques have recently gained popularity in developing predictive models to detect early-stage ovarian cancer. These predictions are made using XAI in a transparent and understandable way for healthcare professionals and patients. The primary aim of this study is to evaluate the effectiveness of various ovarian cancer prediction methodologies. This includes assessing K Nearest Neighbors, Support Vector Machines, Decision trees, and ensemble learning techniques such as Max Voting, Boosting, Bagging, and Stacking. A dataset of 349 patients with known ovarian cancer status was collected from Kaggle. The dataset included a comprehensive range of clinical features such as age, family history, tumor markers, and imaging characteristics. Preprocessing techniques were applied to enhance input data, including feature scaling and dimensionality reduction. A Minimum Redundancy Maximum Relevance (MRMR) algorithm was used to select the features in the model. Our experimental results demonstrate that in Support Vector Machines, we found 85 % base model accuracy and 89 % accuracy after stacking several ensemble learning techniques. With the help of XAI, complex ML algorithms can be given more profound insights into their decision-making, improving their applicability. This paper aims to introduce the best practices for integrating ML and artificial intelligence in biomarker evaluation. Building and evaluating Shapley values-based classifiers and visualizing results were the focus of our investigation. The study contributes to the field of oncology and women's health by offering a promising approach to the early diagnosis of ovarian cancer.

Convolutional neural network algorithm trained on lumbar spine radiographs to predict outcomes of transforaminal epidural steroid injection for lumbosacral radicular pain from spinal stenosis

Little is known about the therapeutic outcomes of transforaminal epidural steroid injection (TFESI) in patients with lumbosacral radicular pain due to lumbar spinal stenosis (LSS). Using lumbar spine radiographs as input data, we trained a convolutional neural network (CNN) to predict therapeutic outcomes after lumbar TFESI in patients with lumbosacral radicular pain caused by LSS. We retrospectively recruited 193 patients for this study. The lumbar spine radiographs included anteroposterior, lateral, and bilateral (left and right) oblique views. We cut each lumbar spine radiograph image into a square shape that included the vertebra corresponding to the level at which the TFESI was performed and the vertebrae juxta below and above that level. Output data were divided into “favorable outcome” (≥ 50% reduction in the numeric rating scale [NRS] score at 2 months post-TFESI) and “poor outcome” (< 50% reduction in the NRS score at 2 months post-TFESI). Using these input and output data, we developed a CNN model for predicting TFESI outcomes. The area under the curve of our model was 0.920. Its accuracy was 87.2%. Our CNN model has an excellent capacity for predicting therapeutic outcomes after lumbar TFESI in patients with lumbosacral radicular pain induced by LSS.

Analysis and Benchmarking of feature reduction for classification under computational constraints

Machine learning is most often expensive in terms of computational and memory costs due to training with large volumes of data. Current computational limitations of many computing systems motivate us to investigate practical approaches, such as feature selection and reduction, to reduce the time and memory costs while not sacrificing the accuracy of classification algorithms. In this work, we carefully review, analyze, and identify the feature reduction methods that have low costs/overheads in terms of time and memory. Then, we evaluate the identified reduction methods in terms of their impact on the accuracy, precision, time, and memory costs of traditional classification algorithms. Specifically, we focus on the least resource intensive feature reduction methods that are available in Scikit-Learn library. Since our goal is to identify the best performing low-cost reduction methods, we do not consider complex expensive reduction algorithms in this study. In our evaluation, we find that at quadratic-scale feature reduction, the classification algorithms achieve the best trade-off among competitive performance metrics. Results show that the overall training times are reduced 61%, the model sizes are reduced 6×, and accuracy scores increase 25% compared to the baselines on average with quadratic scale reduction.

Sedimentary evolutionary processes, architecture, and sedimentary model of a lobate shallow-water delta: insights from flume simulation experiments

By using equipment such as time-lapse cameras and 3D laser scanners, this study conducted flume simulation experiments to obtain topographic elevation, the amount of sediment increment, sedimentary cross sections, and other related data and diagrams. Quantitative software was then utilized for sedimentological analysis to clarify the depositional evolution, architecture, and depositional model of lobate shallow-water deltas. The research results show that under the influence of hydraulic conditions and main distributary channels, lobate shallow-water deltas primarily undergo three evolution stages: initial channel formation, distributary channel system formation, and continuous stable evolution stage. The architecture elements of lobate shallow-water deltas can be divided into distributary channels dominated by channel deposition, proximal river mouth bars, transitional bars, and distal bars. The lateral composition and downstream deposition of the river-bar combination are the main structural units of the shallow water delta. The proximal profile distributary channels exist in the form of thick channel sand bodies with multiple repetitive intercalation cycles, and thick proximal bar deposits form on both sides of the distributary channels. The bifurcation of distributary channels in the middle profile leads to a reduction in channel scale, while large-scale proximal bars still develop on both sides of the channel. In the distal profile, a substantial river mouth bar complex is formed at the break of the delta front slope, and with the gradual progradation of the delta, the river mouth bar deposition zone becomes flattened. Based on the insights of the flume simulation experiments, a sedimentary model for lobate shallow-water delta was established.

Translational research of boron neutron capture therapy for spinal cord gliomas using rat model

Boron neutron capture therapy (BNCT) is a type of targeted particle radiation therapy with potential applications at the cellular level. Spinal cord gliomas (SCGs) present a substantial challenge owing to their poor prognosis and the lack of effective postoperative treatments. This study evaluated the efficacy of BNCT in a rat SCGs model employing the Basso, Beattie, and Bresnahan (BBB) scale to assess postoperative locomotor activity. We confirmed the presence of adequate in vitro boron concentrations in F98 rat glioma and 9L rat gliosarcoma cells exposed to boronophenylalanine (BPA) and in vivo tumor boron concentration 2.5 h after intravenous BPA administration. In vivo neutron irradiation significantly enhanced survival in the BNCT group when compared with that in the untreated group, with a minimal BBB scale reduction in all sham-operated groups. These findings highlight the potential of BNCT as a promising treatment option for SCGs.

A three-way decision method on multi-scale single-valued neutrosophic decision systems

In this paper, we propose a three-way decision (TWD) method on multi-scale single-valued neutrosophic decision systems (MS-SVNDSs). First, to explore the application of single-valued neutrosophic sets (SVNSs) in multi-scale environment, we establish a rough set model of MS-SVNDSs. Then, aiming at the problem of knowledge acquisition in MS-SVNDSs, we present the corresponding optimal scale selection and reduction methods by using evidence theory, a more direct and simpler algorithm is also discussed. For obtaining decision results that are more in line with human cognition, we further provide a novel three-way decision method. Comparative experiments are subsequently conducted to demonstrate the effectiveness of our approach. The experimental results show that our method not only improves the classification accuracy but also raises decision efficiency.

GMP implementation of a hybrid continuous manufacturing process for a recombinant non-mAb protein-A case study.

Advances in manufacturing technology coupled with the increased potency of new biotherapeutic modalities have created an external environment where continuous manufacturing (CM) can address a growing need. Amgen has successfully implemented a hybrid CM process for a commercial lifecycle program. In this process, the bioreactor, harvest, capture column, and viral inactivation/depth filtration unit operations were integrated together in an automated, continuous module, while the remaining downstream unit operations took place in stand-alone batch mode. CM operations are particularly suited for so-called "high mix, low volume" manufacturing plants, where a variety of molecules are manufactured in relatively low volumes. The selected molecule fit this mold and was manufactured in a low-capital micro-footprint suite attached to an existing therapeutic production facility. Use of a hybrid process within an already operating facility required less capital and minimized complexity. To enable this hybrid CM process, an established fed-batch process was converted to a perfusion process with continuous harvest. Development efforts included both process changes and the generation of a novel cell line adapted to long-term perfusion. Chromatography resins were updated, and purification processes adapted to handle variable inputs due to the fluctuations in harvest titer from the lengthy production process. A novel automated single-use (SU) viral inactivation (VI) skid was introduced, which entailed the development of a robust pH verification and alarm system, along with procedures for product isolation to allow discard of specific cycles. The CM process demonstrated consistent performance, meaning it met predefined performance criteria (including product quality attributes, or PQAs) when operated within established process parameters and manufactured according to applicable procedures. Using a 75% reduction in scale, it resulted in a five-fold reduction in process media and buffer usage, a fifteen-fold increase in mass per thaw, and an overall process productivity increase of 45-fold (as measured by grams drug substance per liter per day.) The hybrid CM process also enabled increased material demand to be met with no change in cost of goods manufactured or plant capacity, due to the repurposing of existing facility space and the flexible duration of the hybrid CM harvest. Overall, the success of the hybrid CM platform represents an exciting opportunity to reduce costs and increase process efficiency in industry.

An evaluation of treatment response and remission definitions in adult obsessive-compulsive disorder: A systematic review and individual-patient data meta-analysis

IntroductionExpert consensus operationalized treatment response and remission in obsessive-compulsive disorder (OCD) as a Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) reduction ≥35% and score ≤12 with ≤2 on Clinical Global Impressions Improvement (CGI-I) and Severity (CGI-S) scales, respectively. However, there has been scant empirical evidence supporting these definitions. MethodsWe conducted a systematic review and an individual participant data meta-analysis of randomized-controlled trials (RCTs) in adults with OCD to determine optimal Y-BOCS thresholds for response and remission. We estimated pooled sensitivity/specificity for each percent reduction threshold (response) or posttreatment score (remission) to determine response and remission defined by a CGI-I and CGI-S ≤ 2, respectively. ResultsIndividual participant data from 25 of 94 eligible RCTs (1235 participants) were included. The optimal threshold for response was ≥30% Y-BOCS reduction and for remission was ≤15 posttreatment Y-BOCS. However, differences in sensitivity and specificity between the optimal and nearby thresholds for response and remission were small with some uncertainty demonstrated by the confidence ellipses. ConclusionWhile the empirically derived Y-BOCS thresholds in our meta-analysis differ from expert consensus, given the predominance of data from more recent trials of OCD, which involved more refractory participants and novel treatment modalities as opposed to first-line therapies, we recommend the continued use of the consensus definitions.

New physical insights into the supporting subspace factorization of XMS-CASPT2 and generalization to multiple spin states via spin-free formulation.

This paper introduces a spin-free formulation of the supporting subspace factorization [C. Song and T. J. Martínez, J. Chem. Phys. 149, 044108 (2018)], enabling a reduction in the computational scaling of the extended multi-state complete active space second-order perturbation (XMS-CASPT2) method for arbitrary spins. Compared to the original formulation that is defined in the spin orbitals and is limited to singlet states, the spin-free formulation in this work treats different spin states equivalently, thus naturally generalizing the idea beyond singlet states. In addition, we will present a new way of deriving the supporting subspace factorization with the purpose of understanding its physical interpretation. In this new derivation, we separate the sources that make CASPT2 difficult into the "same-site interactions" and "inter-site interactions." We will first show how the Kronecker sum can be used to remove the same-site interactions in the absence of inter-site interactions, leading to MP2 energy in dressed orbitals. We will then show how the inter-site interactions can be exactly recovered using Löwdin partition, where the supporting subspace concept will naturally arise. The new spin-free formulation maintains the main advantage of the supporting subspace factorization, i.e., allowing XMS-CASPT2 energies to be computed using highly optimized MP2 energy codes and Fock build codes, thus reducing the scaling of XMS-CASPT2 to the same scaling as MP2. We will present and discuss results that benchmark the accuracy and performance of the new method. To demonstrate how the new method can be useful in studying real photochemical systems, the supporting subspace XMS-CASPT2 is applied to a photoreaction sensitive to magnetic field effects. The new spin-free formulation makes it possible to calculate the doublet and quartet states required in this particular photoreaction mechanism.